Hermes has no browser PDF, file upload, or clipboard tools. The fallback
mechanism only covers commands in _FALLBACK_ELIGIBLE (open, snapshot,
screenshot, eval, click, fill, scroll, back, press, console, errors).
The original docs described Lightpanda's general limitations, not
Hermes's actual behavior.
Adds the comment-based hotspot convention (no new primitives) across three
guidance surfaces:
- KANBAN_GUIDANCE worker lifecycle: new step 7 — when a file keeps colliding
with siblings or appears in other cards' recent comments, leave a
'hotspot: <path> — <reason>' kanban_comment and repeat it in completion
metadata so the orchestrator can decompose the file first.
- kanban.md (en + zh-Hans): 'Collision hotspots in parallel campaigns'
subsection — the convention, the orchestrator response (2+ flags on one
path => dedicated decomposition card before queuing more work touching
it), and the cross-link to merge-reconciler for conflicts that already
happened.
- merge-reconciler SKILL.md Pitfalls: repeated conflicts on the same file
across rounds are a hotspot signal — flag for decomposition rather than
serially reconciling.
Live-verified: guidance renders once via real import (6152 chars); hotspot
comment round-trips through add_comment -> list_comments -> worker context
on an isolated HERMES_KANBAN_DB; kanban tools, review-surfaces, and
merge-reconciler skill tests green (45 passed).
Design decisions belong to the orchestrator: decide naming schemes,
schemas, file formats, and API shapes before fanning out; never let two
subtree cards decide the same question; stamp every decision into each
dependent card body since workers cannot see sibling context. Mirrored
in the kanban docs (en + zh-Hans) with an exporter/importer worked
example, and bounded KANBAN_GUIDANCE size with an invariant test.
Add a non-terminal "review" status so a worker that finished implementation
can hand off for human review without abusing kanban_block. The old
kanban_block(reason="review-required: ...") convention routed the handoff
through the unblock-loop breaker, so a normal review -> changes -> review
cycle was falsely escalated to triage.
- kanban_db: request_review (running/ready -> review, non-block, emits
review_requested), reopen_review_task (review -> ready/todo, review_reopened),
complete_task accepts review -> done, and a review_dispatch gate (default off,
shared by the dispatcher loop and the gateway health probe).
- kanban_request_review worker tool + `request-review` / `reopen-review` CLI
verbs; tool wired through toolsets, EXPOSED_TOOLS, _POLISHED_TOOLS.
- Gateway notifier wakes the origin subscriber on review_requested and
block_loop_detected; the subscription survives until done/archived, so every
review cycle re-notifies.
- Dashboard PATCH + bulk route the review transitions (request_review /
reopen_review_task) and render the review column.
- goals.py goal-loop and KANBAN_GUIDANCE recognize review as a terminator.
- Docs (reference tables, user guide, AGENTS.md, zh-Hans mirrors) + tests.
needs_input / failed are unchanged: they still route through kanban_block,
still count toward block_recurrences, and still escalate to triage.
An unset browser.backend ("") now resolves to Browser Use mode whenever
the browser-use CLI is runnable (installed binary or uvx); otherwise the
built-in browser tools are kept so browsing never silently breaks.
Camofox setups always keep the built-in tools (no CDP surface), and
backend: off (including YAML 1.1 bare off -> False) forces the built-in
stack. hermes tools row highlighting follows the same effective-mode
resolution, and tests/tools/ pins CLI discovery off so host uvx installs
can't flip built-in-browser tests.
Adds skills/autonomous-ai-agents/merge-reconciler — a bundled skill teaching
a neutral third-party agent to resolve git merge conflicts between two
agents' branches: gather both diffs + intents, classify each hunk
(disjoint-intent / same-question-different-answer / superseded), resolve
under an impartiality contract, verify, and hand back a per-hunk summary.
Procedure was live-tested end-to-end against a real conflict fixture.
Includes contract tests (tests/skills/test_merge_reconciler_skill.py) and a
kanban docs cross-reference (en + zh-Hans): assign a third neutral profile a
reconciliation card with both conflicted cards as parents.
Surface the existing planner/worker cost-split capability as an explicit
strategy in the docs:
- delegation.md: new 'Cost strategy: frontier planner, inexpensive workers'
subsection under Model Override, with a config.yaml snippet using the
verified delegation.model / delegation.provider keys, the resolution order
(base_url > provider > inherit parent; model applies in all cases, empty =
inherit), and a note that delegate_task has no per-task model parameter —
quality-sensitive tasks should use kanban's per-task override instead.
- kanban.md: matching 'Cost strategy: frontier orchestrator, inexpensive
workers' subsection using the verified per-profile config mechanism
(dispatcher injects profile-scoped HERMES_HOME at worker spawn) and the
existing per-task model_override (--model/--provider, set-model, dashboard).
- zh-Hans mirrors for both pages.
- cli-config.yaml.example: cost tip comment under the delegation section.
Config resolution was live-verified against tools/delegate_tool.py
(_load_config + _resolve_delegation_credentials) with a temp HERMES_HOME:
delegation.model pins children to the sentinel model; with no delegation
keys, children inherit the parent model and credentials.
Adds 'Handing context to follow-up cards (the parent link)' to the kanban
feature page and a CI-remediation worked example to the tutorial, with
zh-Hans mirrors. Claims live-verified against kanban_db on an isolated
board: create_task creates children of done parents directly in ready,
recompute_ready leaves children of open parents in todo, and
build_worker_context surfaces the parent's completion summary and
metadata under '## Parent task results'.
Reframe (per review): browser.backend: browser-use is now a DRIVER over
whatever browser source is configured, not a competing backend choice.
- browser_exec resolves its CDP endpoint through the same chain the
built-in tools use: BU_* env override > BROWSER_CDP_URL/browser.cdp_url
(/browser connect) > the configured cloud provider via browser_tool's
_get_session_info() — sharing the per-task session cache, expiry
replacement, inactivity reaper, and atexit cleanup instead of
duplicating them. Live-validated against Browserbase (session created,
driven, reaped) and gateway-provisioned Browser Use cloud browsers.
- Direct-API Browser Use configs skip provider resolution (the CLI talks
to their cloud natively via BU_AUTOSPAWN); the Nous-gateway variant
resolves through the provider, so subscribers get CLI mode without a
raw BROWSER_USE_API_KEY.
- Camofox: only true fallback — Firefox-based, custom HTTP API, no CDP
surface (its own health probes fail on CDP-schema calls). Active
Camofox setups keep the built-in browser tools even with
backend: browser-use set.
- hermes tools picker: provider rows and the Browser Use row are no
longer mutually exclusive; selecting a provider keeps the driver
choice, and both rows highlight when composed.
- Docs updated for driver-over-source semantics.
Follow-ups on the salvaged Browser Use CLI integration (PR #66476):
- browser_exec runs model-written Python on the host. Strip it at
tool-definition time for sessions whose resolved toolsets exclude
'terminal' so terminal-less surfaces (locked-down messaging configs)
don't silently regain host code execution through the browser toolset.
Session-level gate in model_tools, not a check_fn (check_fn results are
TTL-cached process-wide across sessions).
- Replace the live 'browser-use skill' schema fetch with a pinned helpers
digest: no third-party version-drifting text in the prompt, byte-stable
schema across machines. A/B benchmarked (108 runs, opus-4.8 + kimi-k3,
6 multi-step web tasks x 3 arms x 3 reps): pinned digest matches the
full skill dump 36/36 vs 36/36 at ~equal tokens; both cut total task
tokens ~60% vs the legacy browser_* toolset.
- Docs note for the terminal gate; contributor mapping for salvage.
Personality persistence used to be split per surface: the TUI/desktop wrote
the NAME to display.personality while the CLI/gateway wrote rendered TEXT
into agent.system_prompt (and their /personality none only blanked the
text, leaving the name behind). When #81946 made display.personality
authoritative everywhere, stale names written long ago resurrected
personalities users had turned off - kawaii defaulting on after updating.
- hermes_cli/personality.py: new single owner of personality state.
Built-in personality definitions, neutral-name normalization, rendering,
availability (built-ins overlaid by agent.personalities), overlay
resolution, and the ONLY sanctioned persistence path
(persist_personality -> display.personality; never agent.system_prompt).
- v34 config migration: one-time reset of display.personality to none
(announcing which personality was cleared and how to re-enable), plus a
scrub of agent.system_prompt when it verbatim-equals a known personality
render (machine-written by the old CLI/gateway). Hand-written manual
prompts are never touched.
- All surfaces rewired through the module: CLI /personality (incl. active
marker in the list), gateway /personality, TUI config.set + slash path
(which previously applied without persisting), TUI config.get (reports
the EFFECTIVE personality), completer, hermes config display, and the
tui_gateway health probe.
- cli.py/config duplicates removed: built-ins now defined once; the
desktop mirrors them from one lib module (src/lib/personalities.ts).
- Docs updated: selection lives in display.personality, built-ins always
available, one-time reset note.
Explain that schema.description is model-facing while register_tool(description=...) only populates ToolEntry metadata, and remove the duplicated hello-world description in English and zh-Hans docs.
Refs #60735
Co-authored-by: Shiki <132348332+songshikang0111@users.noreply.github.com>
Per review: upscaling should be the default behavior (like the original
flux-2-pro chain), not agent opt-in. Policy: every image model whose
native output is below ~2MP now sets upscale=True in its catalog —
users never silently get low-res images. Native hi-res models
(Seedream 5 Pro/Lite, Krea 2 Large) stay off to avoid paying to
upscale already-large output.
- FAL catalog: 16 models flipped to upscale=True (klein, z-image,
nano-banana pro/2/2-lite, gpt-image 1.5/2, ideogram v3/v4, recraft
v4/v4.1, qwen image/3, krea-2 medium on FAL, MAI 2.5 pro).
- Krea plugin: per-model upscale defaults (medium + medium-turbo ON at
1.5K native; large OFF at 2K native), precedence explicit kwarg >
image_gen.krea.upscale config > catalog default.
- The 'upscale' tool param remains as a per-call override in both
directions (false = fast draft, true = force on hi-res/edits).
- Video unchanged: opt-in only (default-on would double every video's
cost and latency).
- Sibling tests updated: routing/payload tests pass upscale=False where
the assertion targets the generation submit; catalog test now pins
the native-resolution policy instead of the flux-2-pro snapshot.
The generated-media surface previously had almost no upscaler coverage:
only fal-ai/flux-2-pro chained Clarity Upscaler (hardcoded catalog
default), every other image model returned ~1MP output with no high-res
path, and video had no upscaler at all. Krea's API treats the enhancer
as a standard second pass; this brings the same shape to Hermes.
- image_generate: new optional 'upscale' boolean in the tool schema.
Explicit true chains the backend upscaler on ANY model (including
edits); explicit false disables flux-2-pro's automatic default;
omitted keeps per-model catalog behavior. Response now reports
'upscaled' so the agent knows which resolution it got.
- FAL image path: explicit flag overrides the catalog 'upscale' default
(Clarity Upscaler, 2x). Failure falls back to the native image.
- Krea plugin: upscale=true chains Krea Enhance
(/generate/enhance/krea/enhance, 2x, prompt-guided) through the same
BYO/managed base URL + auth as generation, with a best-effort poll
loop that never fails a successful generation.
- video_generate: new optional 'upscale' boolean; FAL video plugin
chains ByteDance SeedVR2 (fal-ai/seedvr/upscale/video, 2x factor
mode). Providers without upscalers ignore the kwarg per the ABC
contract (documented in both ABCs).
Validation: targeted suites green (123 tests across 6 files, including
new coverage for override-wins/default-kept/failure-fallback on all
three paths); live E2E on direct FAL verified both chains end-to-end
(klein 9b + Clarity upscaled image; pixverse-v6 1s 360p + SeedVR2
upscaled video).
Salvage of PR #17973 by @TKCen (Sebastian Hänisch), re-implemented on
current main to preserve speed/instructions/provider params,
prepare_spoken_text normalization, OPUS_VOICE_PLATFORMS, is_write_denied
path security, microsecond timestamps, and the streaming-TTS gate.
- Split long TTS text into provider-safe chunks instead of truncating
- Pack generated audio against platform upload limits (Discord 10MB,
Telegram 50MB, configurable via tts.delivery_profiles)
- Combine chunks with ffmpeg (OGG/Opus re-encoded, MP3 stream-copied)
- Multi-file delivery when combination fails or would exceed limits
- Remove hard [:4000] truncation from all callers (cli.py, voice.py,
gateway/run.py, gateway/platforms/base.py)
- Gemini TTS raises ValueError instead of silently truncating when
composed prompt exceeds the provider limit
Simplify-code fixes: removed dead all_touched_paths set, added
try/finally for scratch file cleanup on exception, clean error response
on chunk failure instead of leaking stale file_path.
The coverage warning listed bare page ranges, which tells the agent
WHERE the gaps are but not WHAT they contain — its only options were
guessing or OCRing everything. Each gap is now labeled with the last
text extracted before it (usually a section divider page), so the agent
can decide which gaps it actually needs and render/OCR only those.
Gap list capped at 20 entries with a summary line for pathological
alternating documents.
The non-streaming /v1/responses path built function_call and
function_call_output output items with no status field (and no item id),
while the SSE streaming path correctly emits status in_progress ->
completed. Spec-strict OpenAI clients reading the non-streaming output
array could interpret the status-less function_call items as pending
calls the CLIENT must execute — but these tools were already executed
server-side by the Hermes agent and are replayed for structured tool UI
only. Reported by a community user whose GPT-5.6 client concluded 'a
server should not tell an OpenAI client to execute a tool the server
already executed itself'.
- _extract_output_items now stamps status: completed and spec-shaped
item ids (fc_/fco_) on replayed items, matching the streaming path
- test updated to pin status + id shape
- docs example updated + explicit note that output tool calls are
replayed, never pending
Two small config-gated features:
1. Kanban orphaned-card reconciliation (kanban.reconcile_orphans, default
true, config.yaml): a running card with broken claim bookkeeping
(claim_lock or claim_expires NULL — crash mid-claim, manual SQL, DB
restore) is invisible to all existing recovery paths
(release_stale_claims requires claim_expires NOT NULL,
detect_crashed_workers requires host-local lock + pid,
detect_stale_running is config-disabled by default) and shows Running
forever. New reconcile_orphaned_running() pass in kanban_db.py runs
each dispatch_once tick: requeues orphans to ready with an explanatory
comment, closes any leaked run, emits a 'reconciled' event, and defers
when the recorded PID is still alive on this host (never requeue
beside a live worker). Surfaced via DispatchResult.reconciled_orphans.
2. Per-server MCP identity header (mcp_servers.<name>.identity_header,
config.yaml): optional {name, value_from: static|profile, value}
mapping; the header is attached to that server's HTTP/SSE transport
requests. 'static' sends the config value; 'profile' resolves the
active Hermes profile name once at connect time (no per-call
mutation). Explicit per-server headers of the same name (any casing)
win. Invalid blocks warn-and-ignore; stdio servers warn-and-ignore.
Tests: tests/gateway/test_kanban_reconcile_orphans.py (9),
tests/tools/test_mcp_identity_header.py (13), all written first (RED)
then implemented (GREEN). No new HERMES_* env vars.
Inspired by: openai/symphony tracker reconciliation (Apache-2.0) +
Poke per-user MCP identity (idea-level).
Validate a job's configuration BEFORE any agent machinery is constructed:
- missing provider API key (AuthError from a read-only
resolve_runtime_provider probe; skipped when a fallback_providers chain
is configured, since auth-fallback may rescue the run)
- attached skill not ready (skill_view readiness_status=setup_needed —
missing required env vars / commands / credential files)
- delivery platform unknown or unconnected (deliver=local/origin/all are
never checked; gateway-config load failures fail open)
On a failing check run_job returns a [blocked_config]-marked error without
constructing AIAgent/MCP/etc, so a misconfigured job never burns an LLM
call. run_one_job records last_status='blocked_config' and delivers the
alert exactly ONCE across ticks (persisted preflight_alerted bit — the
alert-once shape from the #73506 dead-pin auto-pause); the next healthy
run clears the marker so a future break re-alerts. Every preflight check
fails open: only an affirmative misconfiguration verdict blocks.
Config: cron.preflight (default true); `cron.preflight: false` restores
the old fail-during-run behavior. Documented in the cron user guide and
config defaults.
mark_job_run gains an optional status= override (unblocked call shape
unchanged) and drops preflight_alerted on any successful run.
Tests: tests/cron/test_preflight_config.py (blocked_config + no agent +
single alert across two ticks, healthy job unaffected, recovery clears
dedup, fallback-chain rescue, opt-out restores old behavior, skill
readiness miss, unknown delivery platform, deliver=local never loads
gateway config). Full tests/cron/ + cronjob tool suite green (525 tests).
Ported from: paperclipai/paperclip execution-semantics §5 (MIT);
in-repo precedent: #27948, #73506
Covers the behavior shipped in #80807 (background dispatch for
cronjob action='run') and #80838 (per-run '## Run Context' prompt,
gateway-loop delivery): immediate return with handle, completion
re-entering the conversation, in-flight dedupe, transient context
injection with prompt scanning, and the sync fallbacks.
Inspired by virgiliojr94/book-to-skill (MIT): /learn now picks the skill
shape by the source. Workflows and small sources still get one tight
SKILL.md; books, paper stacks, specs, and large doc corpora get a
knowledge-base layout — a lean always-loaded SKILL.md index plus one
distilled file per chapter/topic under references/, loaded on demand via
skill_view so query cost stays proportional to the answer.
- agent/learn_prompt.py: new _KNOWLEDGE_SKILL_STANDARDS block (index +
per-chapter references/, structure-not-summary distillation, never
reproduce source passages, fold-in instead of duplicating) and a
_SOURCE_HYGIENE block pinning extracted source text as data and
dropping invisible/bidi Unicode (Trojan Source class). Clarified that
the ~200-line cap and hub-skill ban apply to SKILL.md itself, not a
knowledge skill's own references/ files.
- tests: contracts for the knowledge-base layout, the three embedded
standards blocks, and the source-hygiene coverage.
- docs: skills.md documents the knowledge-base shape.
The turn finalizer already hands back steer text that queued after the
final tool batch — result["pending_steer"], with the comment "hand it
back to the caller so it can be delivered as the next user turn instead
of being silently lost." Every interactive surface honors that contract
(cli.py, gateway/run.py, tui_gateway/server.py all requeue it). The
delegation layer doesn't: _run_single_child never reads it, so a steer
queued into a delegated child that finishes first vanishes with no trace
in the completion entry. There is also no sanctioned sender: the registry
has interrupt_subagent() but no redirection-side mirror, and session.steer
cannot reach children (lazy watch sessions have agent=None, so it 4010s).
Complete the contract for delegated children — both halves:
- steer_subagent(subagent_id, text): redirection-side mirror of
interrupt_subagent(). Resolves the live child in _active_subagents and
queues text via AIAgent.steer(). True means queued, not delivered.
- missed_steer retention: when the child's result carries pending_steer,
_run_single_child names it on the completion entry (missed_steer field
plus a summary note) so the parent can re-issue the guidance instead of
trusting it landed. This is what makes adding a sender safe: without it
the finish-before-drain race silently loses the text — the exact loss
the finalizer contract exists to prevent.
- subagent.steer gateway RPC beside subagent.interrupt so programmatic
hosts (dashboard, voice layers, ACP bridges) get an in-tree caller;
catalogued in programmatic-integration.md.
- docs: "Steering a Running Subagent" section in delegation.md covering
the queued-vs-delivered semantics.
Tests: registry-level steer coverage (delivery, unknown id, empty text,
dead record, raising agent), the finish-before-drain race retaining
missed_steer, and the RPC contract (4000/4002 validation, queued and
rejected envelopes).
/heartbeat every <interval> <prompt> gives the current session one
recurring instruction. When the session is idle and the interval has
elapsed, the prompt is injected as a plain user turn — same
conversation, same context, prompt cache and role alternation
untouched.
- CLI: idle-poll watchdog thread (wake-word watchdog pattern) feeding
_pending_input; gateway: single gateway-wide async poller injecting
through the adapter FIFO. Busy sessions coalesce their tick to the
next idle poll.
- Missed ticks coalesce (anchor resets on fire) — a busy hour yields
ONE heartbeat turn, never a backlog. Real user messages always win.
- 60s interval floor; injected prompt carries a don't-invent-work
guard so idle heartbeats don't generate busywork.
- State persists in SessionDB.state_meta (heartbeat:<session_id>),
survives /resume, migrates across compression session rotations
alongside /goal state.
- Session-scoped and in-process by design — durable cross-process
schedules remain the cron subsystem's job (docs draw the boundary).
- Slack stays under the 50-slash cap via /hermes heartbeat; ghost-text
suggester now prefers the shortest prefix match so /he still
suggests /help.
Adapted from the session-heartbeat concept in Prime Intellect's
Prime-Agent (/heartbeat).
/goal gate add <command> attaches shell commands to the active goal.
Gates run at turn boundary BEFORE the LLM judge: a failing gate skips
the judge entirely and feeds its exit code + bounded output tail back
as the continuation prompt, so the agent iterates against concrete
evidence instead of a prose verdict.
- Unchanged-workspace skip: a gate that failed on an identical
workspace (git HEAD + status fingerprint) is not re-run — the
recorded failure replays and the attempt count advances.
- Bounded retries (default 3) + per-gate timeout (default 300s);
exhaustion auto-pauses the goal like the turn budget does.
- Gates persist in SessionDB.state_meta with the goal (survive
/resume and compression rotation); pre-gate goal rows load
unchanged.
- /goal gate [list|add|remove|clear] on CLI + gateway; 'gate' added
to the mid-run control-verb whitelist (gates only run at turn
boundary, so editing the list mid-run is safe).
Adapted from the quality-gate concept in Prime Intellect's Prime-Agent
(--autonomous-gate).
* feat(wake): client-capture wake word for remote desktop
Remote headless backends have no PortAudio mic, so "hey hermes" fails even
when openWakeWord is installed. Let the desktop stream 16 kHz int16 PCM via
wake.feed while detection stays server-side.
- wake_word.capture: auto|local|client (+ GUI client_capture prefer)
- WakeWordDetector external_audio queue + feed_audio API
- wake.feed RPC; wake.start/status report capture + frame_length
- Desktop getUserMedia feeder; stop on wake.detected, re-arm after voice
- Docs + unit tests (26 pass in tests/tools/test_wake_word.py)
* fix(wake): address review on client-capture re-arm and feed queue
- wake.status reports effective capture from the armed detector (client vs
local), plus frame_length/sample_rate; GUI status probes prefer client
- Gateway test doubles accept external_audio on start_listening
- Desktop PCM feeder uses a bounded ordered queue instead of dropping frames
while a wake.feed RPC is in flight
- /wake on and status/re-arm paths pass client_capture so remote reattach works
* fix(wake): auto capture keeps the backend mic when one exists
With capture:auto the desktop always preferred client streaming, so a local
desktop with a working backend mic silently switched from PortAudio to
getUserMedia default-device — dropping wake_word.input_device selection
(#74363). A ready backend input now wins under auto; client capture is the
fallback for a preferring surface on a mic-less backend, and capture:client
still forces streaming.
Also removes the dead auto branch (both arms returned local) and lets the
client-feed test skip cleanly when numpy is absent.
* perf(desktop): coalesce wake.feed frames
Sending one 80 ms frame per RPC is ~12.5 gateway calls/s for as long as the
ear is armed. Drain up to 4 queued frames into a single wake.feed payload
(backend feed() already splits long buffers into engine frames) — ~3 RPCs/s
steady-state. Fix the wake.feed size-cap comment (64000 bytes = 2 s, not
0.5 s).
* docs(config): document wake_word.capture in cli-config.yaml.example
---------
Co-authored-by: Andrew <drew@kainotomic.com>
Remote headless backends have no PortAudio mic, so "hey hermes" fails even
when openWakeWord is installed. Let the desktop stream 16 kHz int16 PCM via
wake.feed while detection stays server-side.
- wake_word.capture: auto|local|client (+ GUI client_capture prefer)
- WakeWordDetector external_audio queue + feed_audio API
- wake.feed RPC; wake.start/status report capture + frame_length
- Desktop getUserMedia feeder; stop on wake.detected, re-arm after voice
- Docs + unit tests (26 pass in tests/tools/test_wake_word.py)
The original PR #78453 said 'A job that was mid-run during a restart
resumes according to the attempt policy described in this page.' This
is misleading — the existing docs explicitly state 'Unknown attempts
are audit records and are never automatically rerun.' Corrected to
accurately describe: the mid-run attempt is marked unknown (not retried),
but the job's next scheduled tick fires normally.
- cron: state explicitly that job definitions survive updates, gateway
restarts and reboots (asked directly in #37542)
- mcp: add a Claude Code bridge tip - mcpServers maps to mcp_servers and
hermes import-agent migrates it (the MCP page never says 'mcpServers'
in the client direction; arrivals from Claude Code get no pointer)
- installation: surface loginctl enable-linger in the non-sudo/service
user section where affected users start (currently only on the
gateway page; #43748)
- sessions: document optimize, optimize-storage, repair, recover and
retitle-skills in the CLI reference (shipped in v0.19.1 --help but
absent from the table) and recommend non-destructive optimize before
prune in the db-growth tip
All wording verified against hermes v0.19.1 --help output and the live
pages on 2026-08-04.
The goals page never mentions Kanban and the kanban page references /goal
only inside the goal-mode-cards section, so users assume /goal hands work
to the board (see #26116 - /goal is single-session continuation only).
Adds a decision section to goals.md and the inverse note to kanban.md.
The reset keywords have existed in both CLI and gateway handlers since
June but were undocumented — users couldn't find how to cancel a
personality overlay. Adds a 'Resetting to the default' section to the
personality feature page and mentions the reset in the CLI guide,
slash-command reference (both tables), and messaging command table.
kshitij
Katie Brown
Teknium
Jakub Wolniewicz
Nikita Barkov
Laith Weinberger
Ken Weiner
kinsolee
SmokeDev
brooklyn!
Andrew
kshitij
witcheer
xxxigm