DeepSeek Harness is an open-source framework for building and running AI agents, organized so that its functionality is provided through plugins. Developers use it to launch agent workflows through a local web interface or from source, while the catalogue add-ons extend the harness as plugins.
Borrowing it
Nothing to install: this file belongs to deepseek-ai/deepseek-harness. 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/deepseek-ai/deepseek-harness/master/.agents/skills/dsh-archive-agent-notes/SKILL.mdgit clone --depth 1 https://github.com/deepseek-ai/deepseek-harnessWrote 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/deepseek-ai/deepseek-harness/dsh-archive-agent-notes)<a href="https://agentmods.dev/skills/deepseek-ai/deepseek-harness/dsh-archive-agent-notes"><img src="https://agentmods.dev/badge/skills/deepseek-ai/deepseek-harness/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/deepseek-ai/deepseek-harness/dsh-archive-agent-notes"><img src="https://agentmods.dev/badge/skills/deepseek-ai/deepseek-harness/dsh-archive-agent-notes.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk pass
- NVIDIA SkillSpector pass
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 | $0.00038 | $0.00602 |
| Sonnet 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 10d 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.
Copies of this mod
7 near-identical copies found in the catalogue:
- dsh-archive-agent-notes — 100% identical, 0 lines differ
- dsh-archive-agent-notes — 100% identical, 0 lines differ
- dsh-archive-agent-notes — 100% identical, 0 lines differ
- dsh-archive-agent-notes — 100% identical, 0 lines differ
- dsh-archive-agent-notes — 100% identical, 0 lines differ
- alego-archive-agent-notes — 94% identical, 8 lines differ
- freddie-archive-agent-notes — 89% identical, 26 lines differ
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 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.
- 10d ago First seen · 69 lines · 76 tokens per session scan A 5500e960a645
dsh-archive-agent-notes is a skill published in the GitHub repository deepseek-ai/deepseek-harness (216,777 stars, last pushed yesterday), licensed MIT. It adds 76 tokens to every session and 1,203 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
handoff
Compact the current conversation into a handoff document for another agent to pick up.
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Build a new skin for the dsh-web skin collection (DSH Web GUI) and publish it into the Skin Center — the first-level settings section — scaffold with scripts/dsh-skin-new, author the v2 skin.json manifest plus skin.css token remap (pure asset directory, no package.json, no build step), validate with scripts/dsh-skin…
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dsh-web-sdk-compatibility
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dsh-web-pet-developer
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