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 digital-stoic-org/agent-skills --skill investigategit clone --depth 1 https://github.com/digital-stoic-org/agent-skillsWrote 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/digital-stoic-org/agent-skills/investigate)<a href="https://agentmods.dev/skills/digital-stoic-org/agent-skills/investigate"><img src="https://agentmods.dev/badge/skills/digital-stoic-org/agent-skills/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/digital-stoic-org/agent-skills/investigate"><img src="https://agentmods.dev/badge/skills/digital-stoic-org/agent-skills/investigate.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 5 Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
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 | $0.00060 | $0.01139 |
| Opus 5 | $0.00030 | $0.00570 |
| Sonnet 5 | $0.00012 | $0.00228 |
| Haiku 4.5 | $0.00006 | $0.00114 |
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 12d 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 — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Investigate
Deep analysis for complex technical problems. Proactive (design-first), not reactive (error-first).
You are investigating: $ARGUMENTS
⚠️ AskUserQuestion Guard
CRITICAL: After EVERY AskUserQuestion call, check if answers are empty/blank. Known Claude Code bug: outside Plan Mode, AskUserQuestion silently returns empty answers without showing UI.
If answers are empty: DO NOT proceed with assumptions. Instead:
- Output: "⚠️ Questions didn't display (known Claude Code bug outside Plan Mode)."
- Present the options as a numbered text list and ask user to reply with their choice number.
- WAIT for user reply before continuing.
Workflow
0.Scope → 1.Decompose → 2.Research → 3.Design → 4.Decide → 5.Persist → 6.Bridge
0. Scope
AskUserQuestion to qualify:
- Problem: What exactly are you trying to achieve?
- Constraints: Environment, stack, access limitations, time budget?
- Success criteria: How will you know it's solved?
Skip if $ARGUMENTS already covers these.
1. Decompose
Break problem into sub-problems. See protocols/decompose.md.
- Issue Tree (MECE): Mutually exclusive, collectively exhaustive breakdown
- Constraint Map: Identify binding constraint (Theory of Constraints — optimize the bottleneck, not everything)
- Unknowns inventory: What don't we know? What assumptions are we making?
Output: Mermaid diagram of sub-problems + dependencies.
2. Research
For each sub-problem, multi-angle investigation. See protocols/research.md.
- WebSearch: Existing solutions, patterns, pitfalls for each sub-problem
- Codebase analysis: Glob/Grep/Read relevant code (if applicable)
- IS / IS NOT (Kepner-Tregoe): Bound the problem space — what is affected vs. not
- Use Task (sub-agents) for parallel research on independent sub-problems
Output: Findings matrix — sub-problem × approach × evidence.
3. Design
Generate 2-3 alternative approaches. See protocols/design.md.
What ships with it
4 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.
- 12d ago First seen · 116 lines · 60 tokens per session scan A 5abd0b91f051
investigate is a skill published in the GitHub repository digital-stoic-org/agent-skills (20 stars, last pushed 6d ago), licensed MIT. It adds 60 tokens to every session and 1,139 once invoked, about $0.0003 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.
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