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 agents/luabagg/agent-skills/brainstorminggit clone --depth 1 https://github.com/luabagg/agent-skillsWhat 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 | $0.00023 | $0.00206 |
| Opus 5 | $0.00012 | $0.00103 |
| Sonnet 5 | $0.00005 | $0.00041 |
| Haiku 4.5 | $0.00002 | $0.00021 |
Grade A, and why
brainstorming 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.
What it actually says
You are in brainstorming mode. Your job is design and alignment, not implementation.
At the start of every session, load the brainstorming skill with the skill tool and follow it exactly.
Hard rules:
- Do not write implementation code, scaffold projects, or invoke implementation skills until the user has approved a design.
- Ask clarifying questions one at a time when needed.
- Propose 2-3 approaches with trade-offs before settling on a design.
- After approval, write the spec and use writing-plans for the implementation plan — not ad-hoc coding.
Keep responses collaborative and exploratory. Prefer higher creativity in ideation while staying precise about constraints and success criteria.
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 · 23 lines · 23 tokens per session scan A 79b327cc4788
brainstorming is an agent published in the GitHub repository luabagg/agent-skills (2 stars, last pushed 3d ago), licensed MIT. It adds 23 tokens to every session and 206 once invoked, about $0.0001 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 2026-08-31.
Other agents, from other repositories
commit
Commit pipeline for skill-map. Handles the FULL workflow: detect what's staged / unstaged, decide whether a changeset is needed (per workspace rules in CONTRIBUTING.md), regenerate spec integrity hashes, ROADMAP cross-references, and the conventional commit itself. The workspace CHANGELOG.md files are generated by…
planner
Owns the angle of an article. Turns a topic into an outline plus the open questions evidence has to answer, and opens the two fronts that produce the piece.
researcher
Answers the outline's open questions with citable sources and hands the evidence downstream for verification.
validator
Verifies the evidence before a single sentence gets written: source tier, measurement conditions, links. Passes only what survives.
writer
Turns the outline and the verified evidence into a finished draft. Owns the prose and nothing else.
publisher
Ships a finished draft: last link pass, publication date, status flipped. The end of the line, mechanical by design.