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/fprochazka/claude-code-plugins/overviewgit clone --depth 1 https://github.com/fprochazka/claude-code-pluginsWhat 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 | $0.00012 | $0.00348 |
| Opus 5 | $0.00006 | $0.00174 |
| Sonnet 5 | $0.00002 | $0.00070 |
| Haiku 4.5 | $0.00001 | $0.00035 |
Grade A, and why
overview 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
Context
${CLAUDE_PLUGIN_ROOT}/scripts/fetch-mr-state.sh --all
Your task
Report the state of the merge request. Take no action and change no code.
Cover the pipeline, the discussion threads, the external commit statuses, and what blocks the merge right now.
Reading the pipeline dump
The script already ran glab-pipeline inspect for you. Read the pipeline summary file printed above first — it names each failed job, its stage, and its failure reason, and it points at the file that explains it.
Then open only the files the summary names: job-logs/<failed-job>.log for a script failure, test-report.json for test failures, lint.json plus merged.yml for a config error, downstream/<bridge>-<id>.json for a failed child pipeline.
Do not read the logs of jobs that passed. A green pipeline needs no log at all.
summary.json in the same directory holds the same summary as structured data, for jq queries.
Invoke the glab-pipeline skill before you run the CLI directly, for example to re-inspect after a new push.
Reading the discussions
glab-discussion dumped one file per thread into the discussions directory listed above. Read those files. Do not fetch the discussions again.
$ARGUMENTS
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 · 33 lines · 12 tokens per session scan A c99fb9aba8cb
overview is a command published in the GitHub repository fprochazka/claude-code-plugins (11 stars, last pushed 4d ago), licensed MIT. It adds 12 tokens to every session and 348 once invoked, about $0.0001 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.