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/ai-debugger-inc/aidb/ci-summarygit clone --depth 1 https://github.com/ai-debugger-inc/aidbWhat 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 | $0.00000 | $0.00179 |
| Opus 5 | $0.00000 | $0.00089 |
| Sonnet 5 | $0.00000 | $0.00036 |
| Haiku 4.5 | $0.00000 | $0.00018 |
Grade A, and why
ci-summary 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
description: Review a CI run's detailed summary and investigate failures/flakes.
Review the provided CI summary, focusing on any failed or flaky tests. Analyze the logs and error messages to identify the root causes of these issues. Summarize your findings, including any patterns or commonalities among the failures.
Review the detailed summary –– and download the associated test log artifacts if needed –– via:
dev-cli ci ${RUN_ID} summary --detailed
The run ID is provider either as command input by the user or derived from session context/gh cli run fetching.
IMPORTANT: You must make use of logging artifacts to perform deep investigations. Use related skills, like the troubleshooting skill, to understand which logs are where and what logs might be most applicable to the issues at hand.
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 · 0 tokens per session scan A 553408071171
ci-summary is a command published in the GitHub repository ai-debugger-inc/aidb (21 stars, last pushed 3mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 179 tokens. 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
monitor-ci
Monitors pull request CI checks until they are resolved (pass or fail).
monitor-ci
You are the orchestrator for monitoring Nx Cloud CI pipeline executions and handling self-healing fixes. You spawn the ci-monitor-subagent subagent to poll CI status and make decisions based on the results.
actions
Command "actions" from openclaw/crabbox, covering actions, subcommands, hydrate, register and dispatch.
thundercheck
../../.thunderbot/thundercheck.md.
thunderin
../../.thunderbot/thunderin.md.
thundersync
../../.thunderbot/thundersync.md.