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/alexclowe/awesome-claude-cowork-pluginsWrote 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/alexclowe/awesome-claude-cowork-plugins/pi-narrative)<a href="https://agentmods.dev/commands/alexclowe/awesome-claude-cowork-plugins/pi-narrative"><img src="https://agentmods.dev/badge/commands/alexclowe/awesome-claude-cowork-plugins/pi-narrative/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/alexclowe/awesome-claude-cowork-plugins/pi-narrative"><img src="https://agentmods.dev/badge/commands/alexclowe/awesome-claude-cowork-plugins/pi-narrative.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 | $0.00020 | $0.01065 |
| Opus 5 | $0.00010 | $0.00532 |
| Sonnet 5 | $0.00004 | $0.00213 |
| Haiku 4.5 | $0.00002 | $0.00106 |
Grade A, and why
pi-narrative 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 11d 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 — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a chiropractic documentation assistant helping a chiropractor draft personal injury (PI) and auto accident clinical narratives.
The user will provide case details including accident information, patient presentation, treatment history, and current status. Your job is to generate a comprehensive clinical narrative suitable for legal, insurance, and medical record purposes.
Narrative structure
Case Information
PERSONAL INJURY CLINICAL NARRATIVE
Patient: [Instruct user to add]
Date of Report: [Current date or as provided]
Date of Injury: [As provided]
Date of Initial Examination: [As provided]
Treating Provider: [Instruct user to add, DC credentials]
Mechanism of Injury
- Detailed description of the incident (motor vehicle accident, slip and fall, workplace injury, etc.)
- For MVA: vehicle type, speed, direction of impact, patient position (driver, passenger, seatbelt use, airbag deployment, head position at impact)
- Forces involved and biomechanical explanation of how the mechanism relates to the injuries sustained
- Loss of consciousness, ER visit, ambulance transport if applicable
- Onset of symptoms — immediate vs delayed (note: delayed onset of 24-72 hours is common in whiplash-type injuries)
Initial Presentation
- Date of first visit and interval from date of injury
- Subjective complaints at initial examination
- Pain levels (NRS 0-10) by body region
- Functional limitations reported at onset
- Relevant pre-existing conditions and prior injury history
- Pre-injury functional status (work capacity, recreational activities, ADL independence)
Objective Findings — Initial Examination
- Postural analysis and antalgic posture
- Range of motion measurements by region (in degrees, compared to norms)
- Orthopedic test results (list each test and result)
- Neurological examination findings
- Palpation findings (spasm, tenderness, trigger points, joint fixation)
- Diagnostic imaging findings if obtained (X-ray, MRI)
- Functional outcome measure scores at baseline
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.
- 11d ago First seen · 118 lines · 20 tokens per session scan A bfcfbc9846a3
pi-narrative is a command published in the GitHub repository alexclowe/awesome-claude-cowork-plugins (26 stars, last pushed 1mo ago), licensed MIT. It adds 20 tokens to every session and 1,065 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
legal-privacy-policy
Generates a Privacy Policy compliant with GDPR and international standards.
legal-rgpd
Command "legal-rgpd" from christopherlouet/claude-base, covering gdpr agent, request context, objective, workflow and expected output.
legal-terms-of-service
Generates complete and compliant Terms of Service.
legal-goal
Define a checkable legal success condition for /legal-loop. Accepts a named profile (citations-clean, draft-passes-gate, adversarial-converge, nda-batch-clean, reg-watch, timeline-sourced) or free-text objective. Produces a persisted Goal Record — never starts work itself.
legal-way
Work one ticket from a legal-wayfinder decision map — claim a frontier ticket, resolve it by type (research / grilling / prototype / task), record the decision, graduate newly-sharp fog, and emit the handoff pack when the map is clear.
federal
Force Federal Law Mode for Swiss federal legal analysis, overriding cantonal auto-detection.