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 skills add skillberry-ai/cap-evolve --skill skillgit clone --depth 1 https://github.com/skillberry-ai/cap-evolveWrote 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/skillberry-ai/cap-evolve/skill)<a href="https://agentmods.dev/skills/skillberry-ai/cap-evolve/skill"><img src="https://agentmods.dev/badge/skills/skillberry-ai/cap-evolve/skill/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/skillberry-ai/cap-evolve/skill"><img src="https://agentmods.dev/badge/skills/skillberry-ai/cap-evolve/skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- 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 | $0.00050 | $0.00499 |
| Opus 5.5 | $0.00020 | $0.00200 |
| Sonnet 5.5 | $0.00010 | $0.00100 |
| Haiku 4.5 | $0.00005 | $0.00050 |
Grade A, and why
<skill-name> 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.
What it actually says
One-sentence statement of what running this skill accomplishes.
When to use this skill
Concrete triggers. What situation in the pipeline calls for it.
Inputs
Read inputs/INPUTS.md. For every input marked NEEDED that is not already
present, ASK THE USER — quote the expected path, the command/options to
obtain it, and any alternatives — and do not fabricate it. RECOMMENDED inputs
may be skipped, with a logged note.
What you must implement
The optimizer agent implements the abstract methods in scripts/abstract.py
(or confirms the project adapter already covers them). Then run scripts/check.py
— it refuses until every method is real and deterministic, and tells you exactly
what is still stubbed.
How to run
python scripts/check.py # gate: must pass first
python scripts/run.py <args> # executes the step; prints a JSON result to stdout
The JSON on stdout is the contract surface — downstream skills (and hosts that can't import Python) consume it directly.
References — load only when you need them
references/concepts.md— grounded background and the reasoning behind the design.references/examples.md— concrete worked examples.references/pitfalls.md— failure modes and important points to watch.
Prompt
prompt/PROMPT.md is the prompt template handed to the using-agent when this
skill drives a model step. Fill its {{placeholders}} from the inputs.
What ships with it
10 files 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 · 47 lines · 50 tokens per session scan A 06dbe4707b12
<skill-name> is a skill published in the GitHub repository skillberry-ai/cap-evolve (65 stars, last pushed today), licensed Apache-2.0. It adds 50 tokens to every session and 499 once invoked, about $0.0002 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 2026-08-30.
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