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 utsavanand/uv-suite --skill uvs-investigategit clone --depth 1 https://github.com/utsavanand/uv-suiteWrote 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/utsavanand/uv-suite/uvs-investigate)<a href="https://agentmods.dev/skills/utsavanand/uv-suite/uvs-investigate"><img src="https://agentmods.dev/badge/skills/utsavanand/uv-suite/uvs-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/utsavanand/uv-suite/uvs-investigate"><img src="https://agentmods.dev/badge/skills/utsavanand/uv-suite/uvs-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 | $0.00045 | $0.00884 |
| Opus 5 | $0.00023 | $0.00442 |
| Sonnet 5 | $0.00009 | $0.00177 |
| Haiku 4.5 | $0.00005 | $0.00088 |
Grade A, and why
uvs-investigate scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- Bash(curl *) How it starts
The opening of the file, as written. The whole thing — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
The bug
$ARGUMENTS
Project context
!cat CLAUDE.md 2>/dev/null || echo "No CLAUDE.md"
Session output directory
Write investigation findings under this directory (scoped to the current session):
!"${CLAUDE_PROJECT_DIR:-.}"/.claude/hooks/uv-out-session.sh
Codebase map
!"${CLAUDE_PROJECT_DIR:-.}"/.claude/hooks/uv-out-best.sh map-codebase.md 60 || echo "No codebase map"
Recent changes (potential cause)
!git log --oneline -15 2>/dev/null || echo "no git"
Latest checkpoint
!cat uv-out/current/checkpoints/latest.md 2>/dev/null | head -30 || echo "No checkpoint"
Investigation methodology
Follow this process strictly:
Phase 1: Reproduce
Before investigating, reproduce the bug. Run the failing test, hit the failing endpoint, trigger the error. If you can't reproduce it, say so and ask for reproduction steps.
Phase 2: Narrow scope
Form a hypothesis about WHERE the bug is:
- Read the error message/stack trace carefully
- Identify the failing component (which file, which function, which layer)
- Check recent changes to that component (
git log --oneline [file]) - Check if the component was modified in the last 5 commits (
git diff HEAD~5 [file])
State your hypothesis explicitly: "I think the bug is in [X] because [Y]."
Phase 3: Test the hypothesis
Verify your hypothesis with the smallest possible test:
- Add a log/print statement
- Write a focused test case
- Run a specific command that isolates the behavior
If the hypothesis is wrong, form a new one. Track what you've ruled out.
Phase 4: Fix or escalate
If you found the root cause within 3 attempts: fix it, run the tests, verify.
If you haven't found it after 3 attempts:
## Stuck: [bug description]
Ruled out:
1. [Hypothesis 1] — wrong because [evidence]
2. [Hypothesis 2] — wrong because [evidence]
3. [Hypothesis 3] — wrong because [evidence]
Remaining possibilities:
- [What I haven't checked yet]
What I need:
- [Specific question or access needed from the human]
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 · 121 lines · 45 tokens per session scan A 79b6cd86527e
uvs-investigate is a skill published in the GitHub repository utsavanand/uv-suite (2 stars, last pushed 2mo ago), licensed MIT. It adds 45 tokens to every session and 884 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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.