Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add AlexanderBZ/claude-status-update/plugin install status-updateWrote 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/alexanderbz/claude-status-update/generate)<a href="https://agentmods.dev/commands/alexanderbz/claude-status-update/generate"><img src="https://agentmods.dev/badge/commands/alexanderbz/claude-status-update/generate.svg" alt="Measured on agentmods" 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 | $0.00012 | $0.00800 |
| Opus 5 | $0.00006 | $0.00400 |
| Sonnet 5 | $0.00002 | $0.00160 |
| Haiku 4.5 | $0.00001 | $0.00080 |
Grade A, and why
generate 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 5d 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.
How it starts
The opening of the file, as written. The whole thing — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Status Update
Generate a categorized standup report from recent Claude Code sessions.
Accepts an optional time range argument: a number followed by h (hours), d (days), or w (weeks). Examples: 24h, 7d, 2w. Defaults to 24h if omitted. Parse the argument into hours (e.g., 7d = 168, 2w = 336). Store the result as $HOURS for use in Step 2.
Step 1: Verify Python 3
Run python3 --version. If the command fails, try python --version instead. If neither succeeds, or the version is below 3.10, print:
Python 3.10+ is required but not installed. Install it from https://python.org and try again.
Then stop. Use whichever command succeeded (python3 or python) for all subsequent steps.
Step 2: Run the parser
Execute (using whichever Python command was found in Step 1):
python3 "${CLAUDE_PLUGIN_ROOT}/scripts/status_update_parser.py" --hours $HOURS
The script writes .status-update/signals.json and prints the file path to stdout. Do not delete this file after reading.
Step 3: Read and parse signals
Use the Read tool to read .status-update/signals.json. Parse its contents as JSON. If the sessions array is empty, inform the user:
No Claude Code activity found in the specified time range.
Then stop.
Step 4: Summarize each session
For each session in the sessions array, spawn a Haiku subagent (model: "haiku") in parallel using the Agent tool. Provide the following prompt to each subagent, filling in the session signals:
You are a work-item extractor. Analyze the following signals from a single Claude Code session and identify each distinct piece of work performed.
Return ONLY a JSON array of objects. Each object has exactly two fields:
- "description": a concise summary of the work in imperative mood (e.g., "Fix login timeout", "Add dark mode toggle")
- "category": exactly one of "bug", "feature", "refactor", "research", or "other"
A single session may contain multiple work items spanning different categories. Combine closely related signals into one work item rather than listing each signal separately.
Do not include any text outside the JSON array. Do not wrap in markdown code fences.
Session signals:
$SESSION_SIGNALS
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.
- 5d ago First seen · 92 lines · 12 tokens per session scan A 65bff9cc9726
generate is a command published in the GitHub repository AlexanderBZ/claude-status-update (5 stars, last pushed 5mo ago), licensed MIT. It adds 12 tokens to every session and 800 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 2026-08-31.
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.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
constitution
Create or update the project constitution from interactive or provided principle inputs.
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.