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dsh-observation-journal
已验证 · 实测可装 Cavan-Ou
功能简介
Zero-touch runtime telemetry for DeepSeek Harness: every session writes its own report card (task/model/tools/failures/duration) into a human-readable journal. 纯观察者运行事实遥测。
可用 — 实测通过,早期项目
Zero-touch runtime telemetry for DeepSeek Harness: every session writes its own report card (task/model/tools/failures/duration) into a human-readable journal. 纯观察者运行事实遥测。 实测能干净安装、正常启动。早期项目,但功能可用。
「已验证」表示我们的自动化 CI 在干净 profile 里实际执行了 dsh plugin add 并启动成功——仅此而已。功能描述与版本兼容性均为作者声明。这不是安全审计,也不代表对第三方代码的背书。
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
安装
装一次目录插件,之后本站所有插件都能让 DeepSeek Harness 自动找、自动装:
dsh plugin add dshbase-catalog 然后对 agent 说「帮我装 dsh-observation-journal」,它会在目录里找到并自动安装。文档:dshbase-catalog · 已验证场景包。
该插件是 GitHub 源码(未发 npm)——直接从仓库装:
Web profile:
dsh plugin --profile web add github:Cavan-Ou/dsh-observation-journal Headless(CLI)profile:
dsh plugin --profile headless add github:Cavan-Ou/dsh-observation-journal 实测报告
验证通过:从 GitHub 源码完成 L1 安装 + L2 加载 + L3 运行(dsh 0.1.0-rc.6)。
使用场景
扩展 agent 的编码能力面——给它一个新工具、工作流或集成,让它接手以前做不了的开发任务。
适合谁
想让 dsh 在真实代码库上像队友一样干活的开发者——能改、能跑、能验证,而不只是回答问题。
二次开发建议
工具/命令面就是缝:暴露更多 SDK 能力、加更聪明的上下文接线,或收紧改代码与验证之间的循环。