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/gtapps/claude-code-hermit/capability-brainstormnpx skills add gtapps/claude-code-hermit --skill capability-brainstormgit clone --depth 1 https://github.com/gtapps/claude-code-hermitWrote 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/gtapps/claude-code-hermit/capability-brainstorm)<a href="https://agentmods.dev/skills/gtapps/claude-code-hermit/capability-brainstorm"><img src="https://agentmods.dev/badge/skills/gtapps/claude-code-hermit/capability-brainstorm.svg" alt="Measured on agentmods" 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 | $0.00087 | $0.01426 |
| Opus 5 | $0.00044 | $0.00713 |
| Sonnet 5 | $0.00017 | $0.00285 |
| Haiku 4.5 | $0.00009 | $0.00143 |
Grade A, and why
capability-brainstorm 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 today.
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 — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Capability Brainstorm
Kill criteria (read before running)
After ≥8 invocations, run:
bun ${CLAUDE_PLUGIN_ROOT}/scripts/proposal.ts metrics .claude-code-hermit --source=capability-brainstorm
Triage-survival < 25% or acceptance < 30% → cut this skill rather than tune it — the signal-to-noise ratio isn't there. INSUFFICIENT output means the ≥8-verdict sample hasn't been reached yet; wait and re-check.
1. Gather capability signals (harness-context — read before dispatch)
These three sources require the main session's harness context and cannot be delegated:
- Skills: use the harness available-skills list loaded in your context — that is authoritative.
- MCPs: call
ListMcpResourcesToolto enumerate currently online MCP tools. - Channels: read
config.json→channelskeys.
2. Dispatch the eval runner
Pass the capability signals from Step 1 in the dispatch prompt. Dispatch claude-code-hermit:skill-eval-runner pointed at ${CLAUDE_PLUGIN_ROOT}/skills/capability-brainstorm/reference.md. Include in the dispatch prompt:
plugin_root:${CLAUDE_PLUGIN_ROOT}(resolved absolute path — the runner needs it for the sibling-scan, since${CLAUDE_PLUGIN_ROOT}is not substituted inreference.mdcontent)skills_list: the harness available-skills list (one skill per line)mcp_tools: theListMcpResourcesTooloutputchannels_keys: thechannelskey list from config.json
The runner reads memory topic files, compiled artifacts, and codebase shape in an isolated context, generates ≤2 ideas (applying the friction + grounding constraints), and returns the structured result.
Eval runner return schema — the runner's return value is a JSON object conforming to this block. The schema is byte-identical in reference.md (producer) and here (consumer); a contract test asserts this.
{
"ideas": [
{
"title": "<short idea title>",
"description": "<one-line description>",
"friction": "<one-sentence operator pain>",
"grounding": ["<item 1>", "<item 2>"],
"effort": "hours|days",
"evidence_summary": "<one-paragraph friction + grounding for proposal-create>"
}
],
"discarded": ["<one-line discarded idea>"],
"inputs_scanned": ["<title or path of each source scanned>"]
}
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.
- today Changed d3bdc3064331
- 3d ago First seen · 134 lines · 87 tokens per session scan A ac0cd2344353
capability-brainstorm is a skill published in the GitHub repository gtapps/claude-code-hermit (73 stars, last pushed today), licensed MIT. It adds 87 tokens to every session and 1,426 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
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.
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.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
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…