Plugin directory / Developer / dsh-observation-journal
dsh-observation-journal
Verified · install-tested on dsh Cavan-Ou
What it does
Zero-touch runtime telemetry for DeepSeek Harness: every session writes its own report card (task/model/tools/failures/duration) into a human-readable journal
Works — verified, early-stage project
Zero-touch runtime telemetry for DeepSeek Harness: every session writes its own report card (task/model/tools/failures/duration) into a human-readable journal It installs cleanly and boots without issues in our testing. It's early-stage but functional.
“Verified” means our automated CI actually ran dsh plugin add in a clean profile and it booted — nothing more. Feature descriptions and version compatibility are the author’s claims. This is not a security audit and not an endorsement of third-party code.
README
dsh-observation-journal
Zero-touch runtime telemetry for DeepSeek Harness: every session writes its own report card.
简体中文版见 README.zh.md
A pure observer plugin (zero tools registered, zero LLM calls, zero agent involvement). When a session ends, it writes the run's facts — task, model tier, tools, failures, duration, status — into a human-readable journal with an auto-updated stats section.
Why it exists
Failures have a recorder (dsh-fail-logger). Successes and run facts didn't. This is the sibling: what happened — not how to solve it, not what to remember. No tools, no injection, no retrieval. The harness writes passively; humans and projects read.
What it is not (boundaries, stated plainly):
| Plugin | Records | Injects back into agent? | Consumption |
|---|---|---|---|
| this | run facts (telemetry) | never | human/project file |
| dsh-task-planner | solutions ("how to solve") | yes (recall) | agent planning |
| dsh-mneme / dsh-memento / dsh-memory | agent memories | yes (retrieval) | agent context |
| dsh-fail-logger | failures | via skill | agent skill loading |
60-second verification
dsh plugin --profile headless add <repo-or-pkg> # or copy the repo as a local bundle
dsh --profile headless "run any small task"
cat ~/.dsh/observations.md # a journal row + stats section appeared
What the output looks like
The journal is the UI. A marker section that survives manual edits, plus an auto-stats block:
<!-- OBS-JOURNAL:BEGIN -->
| time | sid | task | model | dur | turns | tools | calls | fail | status |
|---|---|---|---|---|---|---|---|---|---|
| 2026-08-14T21:42 | abe96e0f | 阅读 specs/s11-1.md 任务书 | deepseek-v4-pro(max) | 1242 | 1 | read:80,bash:12,edit:9,todo_write:4 | 106 | 0 | completed |
| 2026-08-15T03:04 | 9c1f3a | run any small task | deepseek-v4-flash(max) | 25 | 1 | bash:4,grep:2,glob:1 | 7 | 0 | completed |
<!-- OBS-JOURNAL:END -->
<!-- OBS-JOURNAL:STATS -->
- sessions: 2
- failure rate: 0.0%（0/113）
- top tools: read:80,bash:12,edit:9,todo_write:4,grep:2
- avg duration (s) by model: deepseek-v4-flash(max): 25, deepseek-v4-pro(max): 1242
<!-- OBS-JOURNAL:STATS:END -->
raw sidecar (obsFile + '.jsonl', append-only): full fidelity — todo planning trace (≤5), complete tool counts, failed tools, full model id, full task description, normalized task_hash. This is the v2 material for LLM insight; it is TTL-decoupled from the card.
Config (all optional, patch config: field)
| key | default | description |
|---|---|---|
obsFile |
$DSH_HOME/observations.md |
journal path (point it at a project-level file) |
maxRows |
200 |
card keeps last N rows (raw sidecar unaffected) |
marker |
OBS-JOURNAL |
section marker id, [A-Za-z0-9-] |
redact |
[] |
extra redaction regexes (stacked on the built-in secret table) |
flushMs |
300 |
trailing debounce after turn/end |
Env: OBS_FILE overrides obsFile; OBS_REPLAY=<session.jsonl> replays real events (test/CI mode).
Reliability
- 10-column card rows: one row per session — no lossy merging
- Task title escapes
|and newlines; secrets redacted (same table as fail-logger) - Cross-process write lock + stale lock reclaim; dispose fallback flushes sessions with no turn/end
- Tested against real session logs: 14/14 replay tests on 5 real .zstd fixtures (incl. a 2000+ event Pro long-synthesis session), field-by-field cross-checked against independent recomputation; 21-session full replay verified human sections byte-identical
Development
node --check lib/index.js
node --test tests/test.mjs # needs python3 + zstandard
License
MIT
Install
Install the catalog once, then DeepSeek Harness can find and install any plugin from this site automatically:
dsh plugin add dshbase-catalogThen say "install dsh-observation-journal for me" — your agent finds it in the directory and installs it. Docs: dshbase-catalog · verified packs.
This plugin is GitHub source (not published to npm) — install it straight from the repo:
Web profile:
dsh plugin --profile web add github:Cavan-Ou/dsh-observation-journalHeadless (CLI) profile:
dsh plugin --profile headless add github:Cavan-Ou/dsh-observation-journalTest report
Verified: L1 install + L2 load + L3 runtime from GitHub source on dsh 0.1.0-rc.6.
When to use it
Extend the agent's coding surface — give it a new tool, workflow, or integration so it handles a dev task it couldn't before.
Who it's for
Developers who want dsh to behave like a teammate on real codebases — editing, running, and verifying changes rather than just answering.
For developers — extending it
The tool/command surface is the seam: expose more of the SDK, add smarter context wiring, or tighten the loop between code changes and verification.
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Drop this badge into your README — it links back here and updates automatically when our test status changes:
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