Borrowing it
Nothing to install: this file belongs to rajbos/ai-engineering-fluency. 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/rajbos/ai-engineering-fluency/main/.claude/skills/discover-debug-log-schema/SKILL.mdgit clone --depth 1 https://github.com/rajbos/ai-engineering-fluencyWrote 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/rajbos/ai-engineering-fluency/discover-debug-log-schema)<a href="https://agentmods.dev/skills/rajbos/ai-engineering-fluency/discover-debug-log-schema"><img src="https://agentmods.dev/badge/skills/rajbos/ai-engineering-fluency/discover-debug-log-schema/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/rajbos/ai-engineering-fluency/discover-debug-log-schema"><img src="https://agentmods.dev/badge/skills/rajbos/ai-engineering-fluency/discover-debug-log-schema.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 | $0.00107 | $0.01247 |
| Opus 5.5 | $0.00043 | $0.00499 |
| Sonnet 5.5 | $0.00021 | $0.00249 |
| Haiku 4.5 | $0.00011 | $0.00125 |
Grade A, and why
discover-debug-log-schema 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 yesterday.
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 — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Discover Debug Log Schema Skill
Reads VS Code Copilot Chat's debug logs on this machine and reports what is actually in them.
The extension reads copilotUsageNanoAiu out of these logs to bill VS Code Chat
sessions exactly rather than estimating — see
docs/logFilesSchema/vscode-chat-debug-log-format.md.
That format is undocumented by Microsoft, we parse exactly one of its event types,
and validate-session-schemas does not cover it. This skill closes that gap.
What it answers
- Is the billing contract intact? Are the five
llm_requestattrs that_eatdlProcessLlmRequest()insrc/tokenEstimation.tsdepends on (inputTokens,outputTokens,cachedTokens,model,copilotUsageNanoAiu) still present? This matters because a rename fails silently: the parser still returns a result,copilotNanoAiubecomes0, and every affected session quietly falls back to estimated pricing. No test fails, no error surfaces. - What are we leaving on the table? Every event type and field path in the log,
marked
PARSED/IGNOREDper type and*per field for what the repo reads today. We consumellm_requestonly;request_startandrequest_endare known to exist and are parsed by nothing. If those carry timings, per-call latency would be available with no user configuration — nobody has checked.
Usage
Run from the repository root. Dependency-free Node, no build step:
# Default: last 30 days, 10 most-recent logs
node .github/skills/discover-debug-log-schema/discover-debug-log-schema.js
# Every log regardless of age, more files
node .github/skills/discover-debug-log-schema/discover-debug-log-schema.js --days 0 --max 50
# Machine-readable
node .github/skills/discover-debug-log-schema/discover-debug-log-schema.js --json
Options
| Flag | Meaning |
|---|---|
--days N |
Only files modified within the last N days (default 30; 0 = no limit) |
--max N |
Analyze at most N most-recent log files (default 10) |
--include-examples |
Include truncated example values — may contain prompts and file paths |
--json |
Emit JSON only |
--help |
Usage |
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.
- yesterday First seen · 106 lines · 107 tokens per session scan A 0d90ff7f70db
discover-debug-log-schema is a skill published in the GitHub repository rajbos/ai-engineering-fluency (119 stars, last pushed yesterday), licensed MIT. It adds 107 tokens to every session and 1,247 once invoked, about $0.0004 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 2026-10-26.
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