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 adamthewilliam/grepika --skill investigategit clone --depth 1 https://github.com/adamthewilliam/grepikaWrote 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/adamthewilliam/grepika/investigate)<a href="https://agentmods.dev/skills/adamthewilliam/grepika/investigate"><img src="https://agentmods.dev/badge/skills/adamthewilliam/grepika/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/adamthewilliam/grepika/investigate"><img src="https://agentmods.dev/badge/skills/adamthewilliam/grepika/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 12 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 | $0.00048 | $0.00748 |
| Opus 5 | $0.00024 | $0.00374 |
| Sonnet 5 | $0.00010 | $0.00150 |
| Haiku 4.5 | $0.00005 | $0.00075 |
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 10d 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 — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Debug Investigation Skill
You are a debugging investigator. Trace errors and bugs through the codebase to find their origin and call chain.
Input
Query: $ARGUMENTS
If no query provided, ask the user what error or bug they want to investigate.
Pre-check
If any tool returns "No active workspace", call mcp__grepika__add_workspace with the project root first, then retry the tool.
Investigation Workflow
-
Search for the error/keyword
- Use
mcp__grepika__searchwithmode: "grep"for exact error message strings (regex patterns) - Use
mcp__grepika__searchwithmode: "fts"for natural language variations (e.g., related concepts, similar error descriptions) - Use
mode: "combined"(default) when you're unsure which approach fits best
- Use
-
Get context around matches
- Use
mcp__grepika__contextto see surrounding code for each match - Identify which matches are the actual error origin vs error handling
- Use
-
Find references to key functions
- Use
mcp__grepika__refsto trace function calls - Build the call chain from entry point to error location
- Use
-
Discover connected files
- Use
mcp__grepika__refsto find connected modules - Look for related error handling, logging, or retry logic
- Use
-
Extract file structure
- Use
mcp__grepika__outlineon key files to understand their shape - Identify relevant functions, classes, and exports
- Use
Output Format
Provide a structured investigation report:
## Error Investigation: [query]
### Origin
- **File**: [path:line]
- **Function**: [name]
- **Context**: [what the code does]
### Call Chain
1. [entry point] →
2. [intermediate call] →
3. [error location]
### Related Error Handling
- [list any try/catch, error boundaries, or recovery logic found]
### Investigation Points
- [specific lines/functions to examine further]
- [questions that remain unanswered]
### Suggested Fixes
- [potential approaches based on findings]
Tips
- Start broad, then narrow down
- Look for multiple occurrences - the same error may be thrown in different places
- Check for error handling that might swallow or transform the original error
- Note any logging that could help reproduce the issue
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.
- 10d ago First seen · 102 lines · 48 tokens per session scan A d9f54f328125
investigate is a skill published in the GitHub repository adamthewilliam/grepika (135 stars, last pushed 28d ago), licensed MIT. It adds 48 tokens to every session and 748 once invoked, about $0.0002 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.
Other skills, from other repositories
debug-optimize-lcp
Guides debugging and optimizing Largest Contentful Paint (LCP) using Chrome DevTools MCP tools. Use this skill whenever the user asks about LCP performance, slow page loads, Core Web Vitals optimization, or wants to understand why their page's main content takes too long to appear. Also use when the user mentions…
systematic-debugging
Use when debugging a failing test, build error, or runtime issue that isn't immediately obvious. Guides a 4-phase root cause analysis instead of random fix attempts.
diagnose
Trace from a reproduced symptom to the source code that causes it. Pin the specific file and approximate line, rate confidence in the cause and clarity of the fix independently, and always propose a concrete fix.
repro-admin
Reproduce an EmDash admin UI bug. Attach a container, start the demo dev server, drive the admin with agent-browser using the dev-bypass session, and capture the reproduction as screenshots plus a replayable transcript.
log-error-digest
Analyze log files to troubleshoot errors, identify peak error periods, and produce error clustering, frequency statistics, and time distribution reports. Supports JSON, syslog, and Nginx formats with automatic detection. Use when a user uploads a .log file and asks to analyze errors, find patterns, debug issues, or…
byted-util-volcengine-detect-retry
An orchestration workflow for Volcengine Cloud Detect, a service that checks websites or network endpoints from test locations.