Borrowing it
Nothing to install: this file belongs to whitelonng/dshcode. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/whitelonng/dshcode/master/.agents/skills/dsh-archive-agent-notes/SKILL.mdgit clone --depth 1 https://github.com/whitelonng/dshcodeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/whitelonng/dshcode/dsh-archive-agent-notes)<a href="https://agentmods.dev/skills/whitelonng/dshcode/dsh-archive-agent-notes"><img src="https://agentmods.dev/badge/skills/whitelonng/dshcode/dsh-archive-agent-notes/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/whitelonng/dshcode/dsh-archive-agent-notes"><img src="https://agentmods.dev/badge/skills/whitelonng/dshcode/dsh-archive-agent-notes.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00076 | $0.01203 |
| Opus 5.5 | $0.00030 | $0.00481 |
| Sonnet 5.5 | $0.00015 | $0.00241 |
| Haiku 4.5 | $0.00008 | $0.00120 |
Grade A, and why
dsh-archive-agent-notes scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to dsh-archive-agent-notes — 18 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Archive DeepSeek Harness Agent Notes
Reduce the active decision corpus without erasing history that can still guide work. Judge every note semantically; word count and age are discovery aids, never archive criteria.
Read the contracts
Read the Agent Note rules, the archive instructions, and the applicable active lifecycle instructions before classifying. Use current code, configuration, package docs, generated catalogs, newer Agent Notes, and inbound links to establish whether a rationale still owns or constrains anything.
Check supersession when adding a note
Every new Agent Note triggers a scoped audit of active notes covering the same decision, mechanism, or rejected alternative. Classify each full or partial supersession while writing the new note: archive qualifying implemented triplets in the same PR, retain and cross-link partial supersessions or independently useful rationale, reject obsolete proposals, and delete rejected notes that no longer prevent a plausible mistake. Apply the Agent Note consolidation rule when the new owner absorbs every unique proposition; do not defer a known match to a later corpus audit.
Classify by future value
Apply these lifecycle-specific outcomes:
- Implemented — keep active: retain a note when its rationale, alternatives, negative guarantees, durable/wire semantics, ownership boundary, security rule, or reintroduction condition is likely to guide a future change. Length does not matter.
- Implemented — archive: archive a note when the shipped decision is complete and its body is unlikely to guide future work, such as one-off UI chrome, a narrow adapter, a minor closed bug, superseded implementation detail, or process history whose current behavior is obvious elsewhere.
- Proposed — never archive: keep a live proposal active; if it is no longer worth pursuing, reject it with an honest reason and satisfy the rejected lifecycle format.
- Rejected — keep only as a guardrail: retain a rejection only when the losing proposal remains a tempting, meaningful mistake and the note explains why it loses.
- Rejected — delete: delete the whole triplet when the rejected idea is obsolete, superseded, no longer plausible, or unlikely to prevent re-litigation. Repair or delete inbound links.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 69 lines · 76 tokens per session scan A 5500e960a645
dsh-archive-agent-notes is a skill published in the GitHub repository whitelonng/dshcode (704 stars, last pushed 1mo ago), licensed MIT. It adds 76 tokens to every session and 1,203 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to dsh-archive-agent-notes, differing in 18 lines, and is treated as a copy.
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