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/nextgit 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 | $0.00012 | $0.00376 |
| Opus 5 | $0.00006 | $0.00188 |
| Sonnet 5 | $0.00002 | $0.00075 |
| Haiku 4.5 | $0.00001 | $0.00038 |
Grade A, and why
next 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 yesterday.
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
Transition to the next phase in the active playbook session.
Instructions
-
Load session state:
- Read
.profile-playbook/sessions/to find the most recent session - Read
{workspace}/state.yamlto getroleandcurrent_phase
- Read
-
Load role-specific resources:
- Phase guide:
skills/{role}-playbook/references/{domain}-phases.md - Coaching prompts:
skills/{role}-playbook/references/coaching-prompts.md
Domain mapping: sa→sa, po→po, ba→ba, testing→testing, pm→pm, ea→ea, cio→cio, cto→cto, cpo→cpo
- Phase guide:
-
Summarize current phase outputs:
- Scan current phase directory for artifacts created
- List artifacts produced
- Highlight key decisions or findings
-
Provide a coaching moment:
- What SFIA skills were practiced and at what level
- What went well
- Growth tip for next level
-
Update
state.yaml:- Set current phase status to
completed, list artifacts - Set next phase status to
in_progress - Update
current_phase - Append coaching to
coaching_log
- Set current phase status to
-
Introduce the next phase:
- Purpose and activities (from the phases reference)
- SFIA skills that will be practiced
- First question or activity to begin
If already at the last phase, summarize the entire session with a final coaching review.
If the user wants to skip to a specific phase, allow it — update state accordingly.
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.
- yesterday First seen · 44 lines · 12 tokens per session scan A a6ef69131e0d
next is a command published in the GitHub repository baodq97/open-plugin (4 stars, last pushed 3mo ago), licensed MIT. It adds 12 tokens to every session and 376 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.