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/cordis-styling-nitpicking/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/cordis-styling-nitpicking)<a href="https://agentmods.dev/skills/deepseek-ai/deepseek-harness/cordis-styling-nitpicking"><img src="https://agentmods.dev/badge/skills/deepseek-ai/deepseek-harness/cordis-styling-nitpicking/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/cordis-styling-nitpicking"><img src="https://agentmods.dev/badge/skills/deepseek-ai/deepseek-harness/cordis-styling-nitpicking.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 | $0.00069 | $0.01633 |
| Opus 5.5 | $0.00028 | $0.00653 |
| Sonnet 5.5 | $0.00014 | $0.00327 |
| Haiku 4.5 | $0.00007 | $0.00163 |
Grade A, and why
cordis-styling-nitpicking 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 yesterday.
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.
How it starts
The opening of the file, as written. The whole thing — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cordis Ownership and Lifecycle Audit
This is a focused semantic review of Cordis ownership and lifecycle. Start a repository audit from exported plugin entrypoints (apply or a concrete default export invoked by Cordis), then trace module initialization, registered services, listeners, effects, disposers, and transitive calls reachable from those roots. Exclude unrelated helpers, build tools, CLI paths, and tests as finding targets. Read tests and vendored Cordis to establish behavior; report a generated defect against its owning source. Do not report defects in vendored code under this skill.
Sources of truth
- Repository conventions: Cordis ownership requirements.
- Lifecycle and effects: effect acquisition and disposal.
- Services: dependency tracking and service availability.
- Defensive patterns: quiescent teardown and required completion listeners.
Review workflow
- Locate mutable owners, registrations, resource acquisition, and work admission reachable from the requested plugin roots. For large scopes, use independent directory scans, then consolidate findings involving the same consumer and resource.
- Trace ownership through the actual context: in a traceable service method,
this.ctxis the caller's context. Identify who owns each effect and the disposer that releases it. - Trace cleanup through every await to its last service call, emitted event, acknowledged operation, and durable write. Include indirect event delivery and cleanup performed after abort, kill, or cancellation.
- Compare consumer completion with the time each required listener, registry, writer, connection, domain, or transport becomes unusable. Inspect the current Cordis implementation; reverse start order and dependency registration alone do not establish completion order.
- Establish a legal failing interleaving and observable impact. Check existing cancellation, explicit sequencing, and documented discard semantics before reporting. Use controlled promises for reproduction where feasible, and label source-only findings accurately.
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.
- yesterday First seen · 66 lines · 69 tokens per session scan A 697bdf8aced2
cordis-styling-nitpicking is a skill published in the GitHub repository deepseek-ai/deepseek-harness (250,433 stars, last pushed today), licensed MIT. It adds 69 tokens to every session and 1,633 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-10-15.
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code-review
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Manage work in the native DeepSeek Harness Taskboard with exact task ids and optimistic versions. Use when an Agent must inspect project work, claim an eligible todo, record progress or blockers, verify an implementation, submit it for human review, or release its own claim; also use when a human asks how to accept…
industry-research-method
A Chinese-language method for researching an industry by mapping its supply chain, tracking policies and news, and writing sourced reports. It separates the chain into upstream inputs, midstream production, and downstream distribution or use.