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/common-room/claude-plugin/generate-account-plangit clone --depth 1 https://github.com/common-room/claude-pluginWrote 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/common-room/claude-plugin/generate-account-plan)<a href="https://agentmods.dev/commands/common-room/claude-plugin/generate-account-plan"><img src="https://agentmods.dev/badge/commands/common-room/claude-plugin/generate-account-plan.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 | $0.00006 | $0.00689 |
| Opus 5 | $0.00003 | $0.00345 |
| Sonnet 5 | $0.00001 | $0.00138 |
| Haiku 4.5 | $0.00001 | $0.00069 |
Grade A, and why
generate-account-plan scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to generate-account-plan — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generate a comprehensive account plan for "$ARGUMENTS".
Process
-
Full account research — Follow the account-research skill to produce a complete account overview. Pull all available first-party (product), second-party (community), and third-party (intent) signals, CRM data, scores, and RoomieAI research.
-
Stakeholder mapping — Fetch the top 5 contacts at this company sorted by member score descending. Classify each into: Champion, Economic Buyer, Influencer, End User, or Unknown. Use Spark persona data if available; if Spark is unavailable, infer from engagement patterns and activity recency. If no activity data exists either, classify as Unknown.
-
Engagement analysis — Pull all organization activity for the last 90 days (up to 50 activities). Identify trends: is engagement growing, stable, or declining? Which contacts are most active? What channels are they engaging through?
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Web search (supplementary) — If CR data is rich, skip. If data is thin or the user requests it, search for recent company news (last 30 days): funding, acquisitions, product launches, leadership changes, competitive moves.
-
Synthesis — Combine all data into a structured account plan. When the user's company context is available (see
references/my-company-context.md), tailor the executive summary, opportunities, and action items to the user's product and ICP.
Output Format
## Account Plan: [Company Name]
### Executive Summary
[3-4 sentences: relationship status, key opportunity, primary risk, recommended priority]
### Account Overview
| Field | Value |
|-------|-------|
| Industry | ... |
| Size | ... |
| Domain | ... |
| CRM Owner | ... |
| Opp Stage | ... |
| ARR | ... |
| Scores | ... |
### Stakeholder Map
**Champions**
- [Name] — [Title] — [Key signals, last activity date]
**Economic Buyers**
- [Name] — [Title] — [Key signals]
**Influencers**
- [Name] — [Title] — [Key signals]
**End Users**
- [Name] — [Title] — [Key signals]
### Engagement Analysis
[Trend summary: growing/stable/declining, most active contacts, top channels, comparison to 90 days prior if data available]
### Recent News [If web search was run]
[Web search findings with sources and dates]
### Opportunities
1. [Signal-backed opportunity with specific next step]
2. ...
### Risks
1. [Signal-backed risk with mitigation]
2. ...
### Prioritized Action Items
1. [Specific action] — [Owner suggestion] — [Timeline]
2. ...
3. ...
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.
- 6d ago First seen · 76 lines · 6 tokens per session scan A 3a8dbc4a8ae7
generate-account-plan is a command published in the GitHub repository common-room/claude-plugin (3 stars, last pushed 6mo ago), licensed Apache-2.0. It adds 6 tokens to every session and 689 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to generate-account-plan, differing in 0 lines, and is treated as a copy.
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.