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 chandrudp29/skillhub --skill debug-agentgit clone --depth 1 https://github.com/chandrudp29/skillhubWrote 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/chandrudp29/skillhub/debug-agent)<a href="https://agentmods.dev/skills/chandrudp29/skillhub/debug-agent"><img src="https://agentmods.dev/badge/skills/chandrudp29/skillhub/debug-agent/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/chandrudp29/skillhub/debug-agent"><img src="https://agentmods.dev/badge/skills/chandrudp29/skillhub/debug-agent.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 | $0.00034 | $0.00966 |
| Opus 5.5 | $0.00014 | $0.00386 |
| Sonnet 5.5 | $0.00007 | $0.00193 |
| Haiku 4.5 | $0.00003 | $0.00097 |
Grade A, and why
debug-agent 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 1mo 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 — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Debug Agent
A discipline for finding root causes — not symptoms. Skips phases only when explicitly justified.
When to Use
- "This is throwing an error I don't understand"
- "This worked yesterday, now it doesn't"
- "The output is wrong but I don't know why"
- "It works locally but fails in production/CI"
Phase 1 — Build a feedback loop
This is the skill. Without a reproducible signal, everything else is guessing.
Build the tightest possible pass/fail test that exercises the bug:
- Failing unit/integration test
- CLI command with fixture input that shows the wrong output
- Curl / HTTP request that triggers the error
- Minimal script that reproduces the problem
The loop is ready when you can run one command and see the bug reliably.
If you can't reproduce it: ask the user for logs, a stack trace, environment details, or a way to access the failing environment. Do not hypothesize without a loop.
Phase 2 — Gather context
Before touching code, collect:
- Full error message and stack trace (not "it says something about null")
- When it started failing (specific commit? deploy? dependency update?)
- Environment (OS, runtime version, env vars, cloud vs local)
- What changed recently (
git log --oneline -20, recent dep updates) - What's expected vs what's happening (exact expected output vs actual)
Run git bisect if it worked in a known past commit — narrows root cause in minutes.
Phase 3 — Hypothesize before touching code
Generate 3–5 ranked hypotheses. Each must be falsifiable:
"If [X] is the cause, then [changing Y] will make the bug disappear."
Show the ranked list before testing. Prevents anchoring on the first idea.
Common root cause categories (check in this order):
- Input data is different from what's expected (null, wrong type, wrong encoding)
- State from a previous operation is leaking (shared mutable state, unclosed connections)
- Async/concurrency issue (race condition, missing await, callback ordering)
- Environment difference (different versions, missing env var, path issue)
- Off-by-one / boundary condition
- Third-party API changed behavior (silent breaking change)
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.
- 1mo ago First seen · 98 lines · 34 tokens per session scan A d883215b5fbe
debug-agent is a skill published in the GitHub repository chandrudp29/skillhub (14 stars, last pushed 3mo ago), licensed MIT. It adds 34 tokens to every session and 966 once invoked, about $0.0001 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.
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