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-onboardgit 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-onboard)<a href="https://agentmods.dev/agents/gentleman-programming/gentle-pi/sdd-onboard"><img src="https://agentmods.dev/badge/agents/gentleman-programming/gentle-pi/sdd-onboard.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 | $0.00021 | $0.00719 |
| Opus 5 | $0.00010 | $0.00360 |
| Sonnet 5 | $0.00004 | $0.00144 |
| Haiku 4.5 | $0.00002 | $0.00072 |
Grade A, and why
sdd-onboard 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
89% identical to sdd-explore — 34 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 — 49 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the SDD onboard 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.
- Pick or ask for a small, real, low-risk improvement that can demonstrate the full SDD lifecycle.
- Teach by doing: create real artifacts for explore, proposal, spec, design, tasks, apply, verify, and archive where appropriate.
- Keep the walkthrough interactive and concise; explain why each phase exists before doing it.
- Respect strict TDD when project testing capabilities are present.
- Do NOT launch child subagents. Parent/orchestrator owns delegation.
- Return the standard phase envelope with status, executive_summary, artifacts, next_recommended, risks, and skill_resolution.
Memory Contract
This is a guided walkthrough. For each phase you demonstrate, read that phase's input artifacts directly from the active backend (do not wait for the parent to inline them) and persist the artifact you produce, using the same topic-key scheme as the real phases.
Inputs to read (engram/both: use the injected Engram memory read tools for the topic key, then fetch the full observation; openspec: read the file under openspec/changes/{change}/):
- Whichever upstream artifacts the demonstrated step requires, named
sdd/{change}/<phase>(e.g.sdd/{change}/proposal,sdd/{change}/spec).
Persist each demonstrated artifact to the active backend before moving on (mandatory):
engram/both: call the injected Engram save tool with title andtopic_key"sdd/{change}/<phase>",type: "architecture",projectfrom context, andcapture_prompt: falsewhen the tool schema supports it (omit the field if an older schema rejects it).openspec: write/update the corresponding file underopenspec/changes/{change}/.none: walk through the artifacts inline.
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 · 49 lines · 21 tokens per session scan A 36c758ab809f
sdd-onboard is an agent published in the GitHub repository Gentleman-Programming/gentle-pi (415 stars, last pushed yesterday), licensed MIT. It adds 21 tokens to every session and 719 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to sdd-explore, differing in 34 lines, and is treated as a copy.
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