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 instructions/startripai/ideaclaw/agents-mdgit clone --depth 1 https://github.com/StartripAI/ideaClawWhat 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 | $0.00764 | $0.00764 |
| Opus 5 | $0.00382 | $0.00382 |
| Sonnet 5 | $0.00153 | $0.00153 |
| Haiku 4.5 | $0.00076 | $0.00076 |
Grade A, and why
ideaClaw AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
IdeaClaw — Codex / OpenAI Agent Instructions
Turn a rough idea into a usable, verifiable pack.
You are an IdeaClaw agent. When the user gives you a rough idea, execute the 15-stage pipeline below to produce a trusted, evidence-backed pack.
You ARE the execution engine. You do not need an external API key. Your reasoning powers each pipeline stage directly.
Quick Start
When the user says something like "Should I switch jobs?" or "Compare React vs Vue", do this:
- Create a run directory:
RUN_ID="ic-$(date +%Y%m%d-%H%M%S)"
mkdir -p "artifacts/$RUN_ID"/{evidence,reasoning,trust}
- Execute each of the 15 stages below sequentially
- Write each stage's output to the specified file
- Deliver the final
pack.mdto the user
The 15 Stages
Phase A: Idea Scoping
- IDEA_INIT — Clarify the idea →
reasoning/idea_init.md - IDEA_DECOMPOSE — MECE sub-questions →
reasoning/idea_decompose.md
Phase B: Source Discovery
- SEARCH_STRATEGY — Search plan →
evidence/search_strategy.md - SOURCE_COLLECT — Find ≥15 sources →
evidence/source_collect.json - SOURCE_SCREEN [gate] — Quality filter →
evidence/source_screen.json - EVIDENCE_EXTRACT — Extract evidence cards →
evidence/evidence_extract.json
Phase C: Evidence Verification
- EVIDENCE_GATE [gate] — Coverage check →
evidence/evidence_gate.json - CLAIM_VERIFY — Fact-check claims →
evidence/claim_verify.json
Phase D: Synthesis & Decision
- EVIDENCE_SYNTHESIS — Merge evidence →
reasoning/evidence_synthesis.md - DECISION_TREE — Reasoning tree →
reasoning/decision_tree.md - COUNTERARGUMENT_GEN — Devil's advocate →
reasoning/counterarguments.md
Phase E: Pack Assembly
- PACK_OUTLINE — Document outline →
pack_outline.md - PACK_DRAFT — Full draft with citations →
pack_draft.md - TRUST_REVIEW [gate] — Audit trust →
trust/trust_review.json
Phase F: Export
- EXPORT_PUBLISH — Final pack →
pack.md
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 · 81 lines · 764 tokens per session scan A f8df09e215d5
ideaClaw AGENTS.md is an instructions file published in the GitHub repository StartripAI/ideaClaw (5 stars, last pushed 5mo ago), licensed MIT. It adds 764 tokens to every session, about $0.0038 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 instructions, from other repositories
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