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/primeline-ai/universal-planning-framework/interview-plangit clone --depth 1 https://github.com/primeline-ai/universal-planning-frameworkWrote 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/primeline-ai/universal-planning-framework/interview-plan)<a href="https://agentmods.dev/commands/primeline-ai/universal-planning-framework/interview-plan"><img src="https://agentmods.dev/badge/commands/primeline-ai/universal-planning-framework/interview-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 | $0.00012 | $0.01515 |
| Opus 5 | $0.00006 | $0.00758 |
| Sonnet 5 | $0.00002 | $0.00303 |
| Haiku 4.5 | $0.00001 | $0.00152 |
Grade A, and why
interview-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 4d 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 — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Plan Interview
You are interviewing this plan: $ARGUMENTS
Read the plan file and conduct a framework-aware interview. Questions are generated based on the Universal Planning Framework, not generic templates.
Mode Selection
Interactive mode (default): Ask the user questions via AskUserQuestion, one tier at a time.
Self-interview mode (--self flag): Claude answers its own questions autonomously. Useful for hardening a plan without human input. Write answers directly, flag low-confidence answers with [Low confidence].
Pre-Flight
- Read the plan file using the Read tool
- Detect domain: Software, AI/Agent, Business, Content, Infrastructure, Data & Analytics, Research, Multi-Domain
- Identify plan grade: Check which CORE/CONDITIONAL sections exist, estimate current grade (C/B/A)
- Scan for anti-patterns: Quick check against 21 anti-patterns to inform question generation
Question Generation (3 Tiers)
Tier 1: Critical Gaps (ask first)
Questions about missing or weak CORE sections. These block implementation.
| Gap Type | Example Question |
|---|---|
| Missing FAILED conditions | "What kills this project? After how long without progress do you pull the plug?" |
| Vague success criteria | "You say 'improve performance' - what specific number makes this a success vs. failure?" |
| Unvalidated assumptions | "You assume [X] - how will you verify this before Phase [N] depends on it?" |
| No rollback on irreversible change | "If Phase [N] breaks production, what's the undo plan? How long does rollback take?" |
| Missing VALIDATE BY | "Assumption [X] has no validation method. How would you test this cheaply before committing?" |
| Assumed facts (#21) | "You state [X] as fact - is this verified or an assumption? What's the source?" |
| Premature commitment | "For assumption [X], what alternative interpretation haven't you considered? Could [X] mean something different than you think?" |
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.
- 4d ago First seen · 145 lines · 0 tokens per session scan A a7e3df16504b
interview-plan is a command published in the GitHub repository primeline-ai/universal-planning-framework (45 stars, last pushed 10d ago), licensed MIT. It adds 12 tokens to every session and 1,515 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
bug-council
Bug Council — spawn 5 diagnostic specialists in parallel to analyze a hard bug from multiple angles, then synthesize a root cause and fix recommendation.
plan
Plan from the current Fathom session, grounded in a structured intent.
discovery-ping
Discovery-plugin self-test. Exercises the plugin-shipped slash command path so we can capture commandsource/expansiontype values via the hook dumps.
validate
Run the FPF Reference MCP validation contract (index status + tool list + compact route query) and report layered evidence.
pr-check-and-fix
Triage failing PR checks and apply fixes using limps workflows and scripts only.
speckit.tasks
Generate an actionable, dependency-ordered tasks.md for the feature based on available design artifacts.