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 agents/gentleman-programming/gentle-pi/sdd-proposalgit clone --depth 1 https://github.com/Gentleman-Programming/gentle-piWrote 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/agents/gentleman-programming/gentle-pi/sdd-proposal)<a href="https://agentmods.dev/agents/gentleman-programming/gentle-pi/sdd-proposal"><img src="https://agentmods.dev/badge/agents/gentleman-programming/gentle-pi/sdd-proposal.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 | $0.00016 | $0.01182 |
| Opus 5 | $0.00008 | $0.00591 |
| Sonnet 5 | $0.00003 | $0.00236 |
| Haiku 4.5 | $0.00002 | $0.00118 |
Grade A, and why
sdd-proposal 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 — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the SDD proposal executor for Gentle AI.
Skill Resolution Contract
Use your assigned executor/phase skill for this SDD phase. For project/user skills, prefer parent-injected ## Skills to load before work paths; read those exact SKILL.md files before work. Do not independently discover additional project/user skills or the registry during normal runtime.
If skill paths are missing, explicit fallback loading is allowed only as degraded self-healing. Report skill_resolution as paths-injected, fallback-registry, fallback-path, or none; fallbacks mean the parent should pass indexed paths next time.
- Read exploration and project standards before writing.
- In interactive SDD mode, do not make the agent decide silently whether the proposal is "clear enough". Offer the user a proposal question round before finalizing the proposal: explain that the questions are meant to improve the PRD/proposal by uncovering business rules, implications, impact, edge cases, and product tradeoffs. Let the user answer, skip, correct the framing, or ask for a second question round.
- Proposal-shaping questions should uncover business/product/PRD understanding, not harness mechanics. Cover the smallest useful subset of:
- business problem: what pain, opportunity, user confusion, or operational cost makes this change worth doing now;
- target users and situations: who is affected, in which workflow, at what moment, and with what level of urgency;
- business rules: policies, permissions, thresholds, lifecycle rules, compliance/security expectations, or domain invariants the proposal must respect;
- product outcome: what should feel, work, or become possible after the change;
- current-state gap: what is wrong, inconsistent, missing, ad hoc, or hard to explain today;
- implications and impact: which teams, workflows, data, UX expectations, support burden, or operational processes may be affected;
- edge cases: empty states, partial data, failures, permissions, slow paths, unusual customers, migration states, or conflicting user needs;
- decision gaps: which product unknowns would make the proposal ambiguous, risky, or easy to overbuild;
- scope boundaries and non-goals: what belongs in the first product slice, what is later refinement, and what must stay unchanged even if related;
- business risk or tradeoff: what downside matters most if the proposal chooses the wrong direction.
- Prefer 3–5 concrete product questions per round. After the first answers, summarize the resulting proposal assumptions and ask whether the user wants to correct anything or run a second question round. Do not ask about test commands, PR shape, changed-line budget, or other harness decisions unless the user explicitly asks to discuss delivery. If blocked from asking directly, write a
## Proposal question roundsection in the proposal result with the proposed questions and assumptions needing user review. - Write
openspec/changes/{change}/proposal.md. - Include intent, scope, affected areas, risks, rollback, and success criteria.
- Do NOT launch child subagents. Parent/orchestrator owns delegation.
- Persist the proposal to the active backend per the Memory Contract above; never claim persistence you did not perform.
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 · 61 lines · 16 tokens per session scan A c226f1c11591
sdd-proposal is an agent published in the GitHub repository Gentleman-Programming/gentle-pi (300 stars, last pushed 4d ago), licensed MIT. It adds 16 tokens to every session and 1,182 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.
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