Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/hkuds/openopc/skill-evolutionnpx skills add HKUDS/OpenOPC --skill skill-evolutiongit clone --depth 1 https://github.com/HKUDS/OpenOPCWhat 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 | $0.00038 | $0.00539 |
| Opus 5 | $0.00019 | $0.00269 |
| Sonnet 5 | $0.00008 | $0.00108 |
| Haiku 4.5 | $0.00004 | $0.00054 |
Grade A, and why
skill-evolution 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 2d 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.
How it starts
The opening of the file, as written. The whole thing — 51 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Evolution
Distill project experience into reusable skills that live under the current project.
Two evolution paths
- Automatic: The system promotes playbook skills when an employee's pattern reaches 2 project reflections with recurring behaviors, checklists, or preferences. These are saved as
<employee>-<role>-<domain>-playbookand require no manual action. - Agent-driven (this skill): You proactively identify valuable patterns and create skills manually. Use this when domain knowledge, workflows, or tool sequences should be preserved before the auto-promotion threshold is reached, or when the knowledge is not tied to a specific employee pattern.
When to evolve a skill (agent-driven)
- A task required non-obvious steps that will likely recur
- You discovered a workflow that worked well and should be preserved
- Domain-specific knowledge was gathered that future tasks will need
- A sequence of tool calls forms a reliable pattern worth codifying
Process
- Identify the pattern: What knowledge or workflow is worth preserving?
- Read the skill-creator skill:
file_readtheskill-creator/SKILL.mdfor format and naming guidelines - Name the skill: Lowercase letters, digits, and hyphens only, under 64 characters (e.g.,
api-validation-workflow) - Create the skill directory: Under
.opc/projects/<project_id>/skills/<skill-name>/ - Write SKILL.md with proper frontmatter (
name,description) and concise instructions - Add scripts/references/assets if the skill benefits from bundled resources
Skill location
Evolved skills belong to the project that produced them:
.opc/projects/<project_id>/skills/<skill-name>/SKILL.md
Guidelines
- Keep it concise: only include what the agent doesn't already know
- Use concrete examples over abstract explanations
- Include the minimal set of steps needed to reproduce the workflow
- Add
scripts/for deterministic operations that get rewritten repeatedly - Add
references/for domain docs the agent should consult - Follow the same naming conventions as auto-promoted skills (hyphen-case)
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.
- 2d ago First seen · 51 lines · 38 tokens per session scan A bc754b6d94b1
skill-evolution is a skill published in the GitHub repository HKUDS/OpenOPC (1,594 stars, last pushed yesterday), licensed MIT. It adds 38 tokens to every session and 539 once invoked, about $0.0002 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
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
agent-host-chat-contributions
Build and review cross-cutting agent-host chat behavior through lifecycle contributions. Use when adding turn lifecycle side effects, prompt or context injection, restored-history transformation, protocol-action observation, or when reviewing changes that add code to AgentSideEffects or AgentService.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.