Development & Runtime

dsh-observation-journal

Cavan-Ou/dsh-observation-journal · ★ 3

Cavan-OuCurated

Zero-touch runtime telemetry for DSH: every session auto-writes task, model tier, tools, failures, duration, status into a human-readable journal with a stats section (pure observer — no tools, no LLM calls, no injection).

License
MIT
Added
2026-08-16
Maintenance
active
Install kind
github
Manifest details
Manifest status
Declared
Manifest path
dsh.plugin.json
Manifest checked
2026-08-19
Lifecycle scripts
None found

Static manifest checks report declarations only; they are not compatibility or security review.

安装

dsh plugin --profile web add github:Cavan-Ou/dsh-observation-journal

GitHub 源码安装:首次需按提示配置 allowBuilds 构建授权后重试

For install and environment setup, plus plugin development tutorials, see DSH community docs ↗

README

Source README · body: en · Read Chinese README

Table of contents
  1. Why it exists
  2. 60-second verification
  3. What the output looks like
  4. Config (all optional, patch config: field)
  5. Reliability
  6. Development
  7. License

Zero-touch runtime telemetry for DeepSeek Harness: every session writes its own report card.

MIT DSH dsh-plugin

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