Borrowing it
Nothing to install: this file belongs to TechHU-GS/cc-discipline. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/TechHU-GS/cc-discipline/main/.claude/skills/investigate/SKILL.mdgit clone --depth 1 https://github.com/TechHU-GS/cc-disciplineWrote 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/techhu-gs/cc-discipline/investigate)<a href="https://agentmods.dev/skills/techhu-gs/cc-discipline/investigate"><img src="https://agentmods.dev/badge/skills/techhu-gs/cc-discipline/investigate/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/techhu-gs/cc-discipline/investigate"><img src="https://agentmods.dev/badge/skills/techhu-gs/cc-discipline/investigate.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00041 | $0.01768 |
| Opus 5.5 | $0.00016 | $0.00707 |
| Sonnet 5.5 | $0.00008 | $0.00354 |
| Haiku 4.5 | $0.00004 | $0.00177 |
Grade A, and why
investigate 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 2mo 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 — 193 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Mode detection
Determine which mode based on user input:
- Research mode — User gives a topic/question with no existing proposal. Goal: build comprehensive understanding before forming an opinion.
- Review mode — User gives an existing document, proposal, or design. Goal: stress-test it from multiple angles, find blind spots and weaknesses.
- Simulate mode — User gives a plan and wants to "dry run" it. Goal: walk through execution step by step, let hidden problems surface naturally.
State which mode you're using and why.
Research Mode
You are about to research a topic or design a solution. Do NOT go deep on one angle. Your job is to see the full picture before converging.
Step 1: Decompose into dimensions
Before researching anything, identify 3-5 independent dimensions of the problem. Ask yourself:
- What are the different angles this could be viewed from?
- What are the stakeholders / affected systems / competing concerns?
- What would a devil's advocate focus on?
Output the dimensions as a numbered list. Each dimension should be genuinely different, not sub-points of the same thing.
Example for "should we migrate from REST to GraphQL?":
- Performance & scalability — latency, payload size, caching implications
- Developer experience — learning curve, tooling, debugging
- Existing ecosystem — what breaks, migration cost, backward compatibility
- Security — query complexity attacks, authorization model changes
- Business — timeline pressure, team skills, client requirements
Step 2: Parallel investigation
Spawn one subagent per dimension. Each agent:
- Investigates ONLY its assigned dimension
- Reads relevant code/docs for that angle
- Lists findings with evidence (file paths, code references, data)
- Flags risks and unknowns specific to that dimension
- Does NOT try to propose a final solution — just reports findings
Launch agents in parallel, not sequentially.
Step 3: Synthesize
After all agents return, synthesize in the main conversation:
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.
- 2mo ago First seen · 193 lines · 41 tokens per session scan A 7768d38e43f8
investigate is a skill published in the GitHub repository TechHU-GS/cc-discipline (0 stars, last pushed 1mo ago), licensed MIT. It adds 41 tokens to every session and 1,768 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 2026-08-31.
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