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 tobihagemann/turbo --skill investigategit clone --depth 1 https://github.com/tobihagemann/turboWrote 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/tobihagemann/turbo/investigate)<a href="https://agentmods.dev/skills/tobihagemann/turbo/investigate"><img src="https://agentmods.dev/badge/skills/tobihagemann/turbo/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/tobihagemann/turbo/investigate"><img src="https://agentmods.dev/badge/skills/tobihagemann/turbo/investigate.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00046 | $0.03308 |
| Opus 5.5 | $0.00018 | $0.01323 |
| Sonnet 5.5 | $0.00009 | $0.00662 |
| Haiku 4.5 | $0.00005 | $0.00331 |
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 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 — 203 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Investigate
Systematic methodology for finding the root cause of bugs, failures, and unexpected behavior. Cycle through characterize-isolate-hypothesize-test steps, with oracle escalation for hard problems. Diagnose the root cause — do not apply fixes.
Optional: $ARGUMENTS contains the problem description or error message.
Step 1: Characterize
Gather the symptom and establish what is actually happening:
- Collect evidence — error message, stack trace, test output, log entries, or user description of unexpected behavior
- Classify the problem type:
| Signal | Type |
|---|---|
| Stack trace / exception | Runtime error |
| Test assertion failure | Test failure |
| Compilation / bundler / build error | Build failure |
| Type checker error (tsc, mypy, pyright) | Type error |
| Slow response / high CPU / memory growth | Performance |
| "It does X instead of Y" / no error | Unexpected behavior |
- Establish reproduction — run the failing command, test, or operation, and confirm its output shows the reported symptom rather than a neighboring failure. When no command at hand shows the symptom, build one, trying whichever of these fit, in this order:
- A test at the boundary that reaches the failure
- A script that drives the running system from outside and asserts on what it returns
- A captured request, payload, or event log replayed through the failing path
- The same input run through a known-good version and the current one, with the outputs compared
- Many generated inputs, when the failure appears for only some
- For an intermittent failure, the trigger repeated or run concurrently until it fails often enough to test against
Reproduction is established when one command has been run and its output shows the reported symptom. Record that command and its output for verification. For intermittent or long-running reproductions, use the Monitor tool to tail logs filtered for relevant signals (errors, stack traces, specific identifiers) so failures surface live while you work.
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.
- 2d ago Changed · +16 lines ef7d95413d8e
- 3d ago Changed · -61 tokens per session f5c6ab90018b
- 20d ago Changed · +2 lines 0bb05aff6c8f
- 1mo ago Changed · +8 lines 07f86ea893db
- 1mo ago Changed · +2 lines 6b3917f3a734
- 2mo ago Changed · +2 lines afc58a5a1309
- 2mo ago First seen · 173 lines · 107 tokens per session scan A 7dc7763929a5
investigate is a skill published in the GitHub repository tobihagemann/turbo (420 stars, last pushed today), licensed MIT. It adds 46 tokens to every session and 3,308 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 2026-08-30.
investigate compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| investigatetobihagemann/turbo | Skill | 420 | today | MIT | A | 46 | Claude Code |
| incident-postmortemmohitagw15856/pm-claude-skills | Skill | 1.5k | today | MIT | A | 87 | Claude Code, Codex |
| agent-incident-postmortemmohitagw15856/pm-claude-skills | Skill | 1.5k | today | MIT | A | 120 | Claude Code |
| agent-design-reviewmohitagw15856/pm-claude-skills | Skill | 1.5k | today | MIT | A | 91 | Claude Code |
| prompt-debuggingmohitagw15856/pm-claude-skills | Skill | 1.5k | today | MIT | A | 131 | Claude Code |
| prompt-optimizermohitagw15856/pm-claude-skills | Skill | 1.5k | today | MIT | A | 86 | Claude Code |
| rag-architecture-reviewmohitagw15856/pm-claude-skills | Skill | 1.5k | today | MIT | A | 89 | Claude Code |