Borrowing it
Nothing to install: this file belongs to svnscha/dap-dbgeng. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/svnscha/dap-dbgeng/develop/.claude/skills/dap-analyze-trace/SKILL.mdgit clone --depth 1 https://github.com/svnscha/dap-dbgengWrote 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/svnscha/dap-dbgeng/dap-analyze-trace)<a href="https://agentmods.dev/skills/svnscha/dap-dbgeng/dap-analyze-trace"><img src="https://agentmods.dev/badge/skills/svnscha/dap-dbgeng/dap-analyze-trace/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/svnscha/dap-dbgeng/dap-analyze-trace"><img src="https://agentmods.dev/badge/skills/svnscha/dap-dbgeng/dap-analyze-trace.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 | $0.00033 | $0.02006 |
| Opus 5.5 | $0.00013 | $0.00802 |
| Sonnet 5.5 | $0.00007 | $0.00401 |
| Haiku 4.5 | $0.00003 | $0.00201 |
Grade A, and why
dap-analyze-trace scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 206 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DAP Analyze Trace
Use this workflow when the user provides a recorded session trace, describes a live debugging failure, and wants the investigation driven by the real request and event flow before deciding whether code changes are needed.
A trace is the JSON file written when a launch/attach configuration sets a trace
path (for example "trace": "${workspaceFolder}/recordings/session.json"). It has the
{ "version", "messages": [ { direction, message } ] } shape - the same format as the
replay fixtures under tests/replay/data.
This skill is intentionally human-in-the-loop. The first pass is for trace formatting, protocol analysis, and a focused code fix or clarification request. Do not create a new replay fixture or automated regression test from the first failing trace. First fix the implementation based on the trace plus the user's description, then ask the user to rerun the live scenario. Only if that rerun succeeds should the fresh trace become an automated replay back-test.
Principles
- Start from the user's reported live behavior, not from a guessed test scenario.
- Format the trace first so request, response, and event ordering are easy to inspect before reasoning about code.
- Treat the trace as evidence of protocol ordering, timing, and state transitions.
- Do not claim the bug is fixed because a synthetic or partial test passes while the live scenario still fails.
- Keep the first implementation change focused on the behavior the user described and the trace supports.
- Ask for missing reproduction details if the trace and description are insufficient to identify the owning code path.
- Do not create a new recorded-session fixture or replay test from the initial failing trace.
- After making a fix, ask the user to rerun the real scenario and provide a fresh trace.
- Only after the user confirms the live scenario behaves correctly should the fresh trace become the source for automated back-testing.
Required First Step
Before analyzing code, format the trace with the repository script:
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.
- 2mo ago First seen · 206 lines · 33 tokens per session scan A 4033a3db7ca6
dap-analyze-trace is a skill published in the GitHub repository svnscha/dap-dbgeng (11 stars, last pushed 1mo ago), licensed MIT. It adds 33 tokens to every session and 2,006 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 2026-08-31.
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