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 agentmods add commands/botpress/skills/adk-debuggit clone --depth 1 https://github.com/botpress/skillsWhat 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 | $0.00009 | $0.00325 |
| Opus 5 | $0.00005 | $0.00162 |
| Sonnet 5 | $0.00002 | $0.00065 |
| Haiku 4.5 | $0.00001 | $0.00032 |
Grade A, and why
adk-debug 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 2d 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.
What it actually says
Load the adk-debugger and adk skills, then start debugging immediately.
If $ARGUMENTS is vague ("broken", "not working", "slow", "weird", or empty), don't ask "what's wrong?" — investigate first. Run adk check --format json and adk logs error --format json, then present what you found.
If $ARGUMENTS mentions a specific component ("the search tool", "my workflow"), go directly to traces filtered by that component.
If $ARGUMENTS contains a pasted error or stack trace, read the file at the referenced line number immediately.
Debug Workflow
- Run
adk check --format jsonto rule out offline issues first. - Reproduce with
adk chat --single "<relevant message>" --format json. - Read traces and logs:
adk logs error --format json,adk traces --format json. - Identify root cause using the debug workflow from the skill.
- Suggest a targeted fix.
- Verify the fix with another
adk chatoradk check. - Write a regression eval for the bug — load the
adk-evalsskill, generate the eval file using the reproduction message as the user turn and the verified behavior as assertions, save it toevals/, and runadk evals <name>to confirm it passes.
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.
- 2d ago First seen · 24 lines · 9 tokens per session scan A af0141091de9
adk-debug is a command published in the GitHub repository botpress/skills (11 stars, last pushed 1mo ago), licensed MIT. It adds 9 tokens to every session and 325 once invoked, about $0.0000 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 commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.