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.
git clone --depth 1 https://github.com/rhan1/crewlineWrote 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/commands/rhan1/crewline/agents)<a href="https://agentmods.dev/commands/rhan1/crewline/agents"><img src="https://agentmods.dev/badge/commands/rhan1/crewline/agents/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/commands/rhan1/crewline/agents"><img src="https://agentmods.dev/badge/commands/rhan1/crewline/agents.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 | $0.00023 | $0.00452 |
| Opus 5.5 | $0.00009 | $0.00181 |
| Sonnet 5.5 | $0.00005 | $0.00090 |
| Haiku 4.5 | $0.00002 | $0.00045 |
Grade A, and why
agents 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.
What it actually says
Show the status of native Claude Code subagents across all recent sessions —
which are running, which finished, what each was tasked with, and a rough
completion count. This reads the subagent transcripts Claude Code maintains at
~/.claude/projects/<project>/<sessionId>/subagents/agent-<id>.jsonl, so it
works even for agents launched from another window and even when a session is
rate-limited. No hooks required.
Procedure
-
Run the scanner, passing through any arguments:
python3 ~/.claude/scripts/agents-status.py $ARGUMENTS -
Present its output to the user as-is (it is already a formatted table). Do not re-summarize unless the user asks — the table is the deliverable.
-
If the user wants a true per-task completion percentage (not just running/done counts), remind them that native subagents are opaque — the reliable way to get
done/total %is the manager-mode convention: the orchestrator callsTaskCreateonce per work-item before fanning out, and each worker callsTaskUpdate(in_progress → completed). That populates the native bottom task tracker with a livedone/total.
Notes
- "RUNNING" = a transcript written within the last
--run-windowsecs (default 90). A long-thinking agent that hasn't written a tool call recently may show as idle — the "last write … ago" column makes this transparent. - The bold name (e.g.
graceful-skipping-galaxy) is Claude Code's auto-generated friendly handle, not the agent type. The task line conveys purpose. --lookbackcontrols how far back finished agents are listed (mins; default 720).
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 · 38 lines · 23 tokens per session scan A 06380f2d1583
agents is a command published in the GitHub repository rhan1/crewline (2 stars, last pushed 11d ago), licensed MIT. It adds 23 tokens to every session and 452 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.
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.
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.
speckit.bug.fix
Apply the remediation from a bug assessment and record what was changed.