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/baodq97/open-plugin/assessgit clone --depth 1 https://github.com/baodq97/open-pluginWhat 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 | $0.00013 | $0.00397 |
| Opus 5 | $0.00006 | $0.00198 |
| Sonnet 5 | $0.00003 | $0.00079 |
| Haiku 4.5 | $0.00001 | $0.00040 |
Grade A, and why
assess 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 2d 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
Assess a document against SFIA criteria for the active role.
Instructions
-
Determine the role:
- Read
.profile-playbook/sessions/to find the most recent session - Read
{workspace}/state.yamlto get therolefield - If no active session, ask the user which role to assess against (sa, po, ba, testing, pm, ea, cio, cto, cpo)
- Read
-
Load role-specific assessment resources:
- Assessment rubric:
skills/{role}-playbook/references/assessment-criteria.md - SFIA skill map:
skills/{role}-playbook/references/sfia-skill-map.md
- Assessment rubric:
-
Get the document to assess:
- If a file path is provided as argument, read the file
- If no argument, ask the user to provide or paste the document
-
Evaluate the document:
Identify demonstrated SFIA skills using the role's skill map — look for evidence of each skill in the document.
Score each skill on 4 dimensions:
- Completeness — coverage of required elements
- Depth — analysis thoroughness
- Communication — clarity and audience appropriateness
- Decision quality — rationale and alternatives documentation
-
Output the assessment using the format in the assessment criteria reference:
- Overall summary
- Skill ratings with estimated SFIA level
- Dimension scores with evidence
- Strengths (with specific examples from the document)
- Gaps (with specific recommendations)
- Actionable recommendations for level-up
Keep the assessment constructive — highlight strengths before gaps.
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.
- 2d ago First seen · 43 lines · 13 tokens per session scan A e02320939697
assess is a command published in the GitHub repository baodq97/open-plugin (4 stars, last pushed 3mo ago), licensed MIT. It adds 13 tokens to every session and 397 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
security-audit-static
Static security audit of AI-built code — map trust boundaries, cross-reference documented intent, self-refute every finding, and report only evidence-backed risks.
performance-audit-static
Static performance audit of AI-built code — find N+1 queries and request waterfalls, over-fetching, missing indexes, and caching opportunities, ranked by effort and impact.
sprint
Sprint lifecycle — plan a sprint, run a retrospective, or generate release notes.
document-app
Reverse-engineer an AI-built codebase into the system documents reviewers and auditors need — a core set (architecture, flows, permissions, variables) plus conditional docs (emails, cron, SEO, automation) when they apply.
analyze-test
Analyze A/B test results — statistical significance, sample size validation, and ship/extend/stop recommendations.
plan-okrs
Brainstorm team-level OKRs aligned with company objectives — qualitative objectives with measurable key results.