Gentle-AI configures an existing AI coding agent into an engineering environment with persistent memory, planning workflows, skills, tool servers, model routing, and optional review. Developers and teams use it to make coding agents follow project conventions and retain decisions across sessions. The catalogue entries are its skills, commands, agents, and instruction.
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.
git clone --depth 1 https://github.com/Gentleman-Programming/gentle-aiWrote 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/gentleman-programming/gentle-ai/gentle-sdd-init)<a href="https://agentmods.dev/commands/gentleman-programming/gentle-ai/gentle-sdd-init"><img src="https://agentmods.dev/badge/commands/gentleman-programming/gentle-ai/gentle-sdd-init.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 | $0.00014 | $0.00312 |
| Opus 5 | $0.00007 | $0.00156 |
| Sonnet 5 | $0.00003 | $0.00062 |
| Haiku 4.5 | $0.00001 | $0.00031 |
Grade A, and why
gentle-sdd-init 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
100% identical to sdd-init — 26 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.
What it actually says
If the native sdd-init sub-agent is available, delegate this command to it.
Otherwise, read the skill file at ~/.claude/skills/sdd-init/SKILL.md FIRST, then follow its instructions exactly inline.
CONTEXT:
- Working directory: Detect agent-side before proceeding by running
git rev-parse --show-toplevelwith the Bash tool; if that fails, runpwdwith the Bash tool. - Current project: Derive agent-side from the detected working directory basename. Do not use slash-command shell interpolation for this value.
- Artifact store mode: engram
TASK: Initialize Spec-Driven Development in this project. Detect the tech stack, existing conventions, and architecture patterns. Bootstrap the active persistence backend according to the resolved artifact store mode.
ENGRAM PERSISTENCE (artifact store mode: engram): After detecting the project context, save it: mem_save(title: "sdd-init/{project}", topic_key: "sdd-init/{project}", type: "architecture", project: "{project}", capture_prompt: false, content: "{detected context}") Set capture_prompt: false when the Engram tool schema supports it; if an older schema rejects or does not expose the field, omit it rather than failing. topic_key enables upserts — re-running init updates, not duplicates.
Return a structured result with: status, executive_summary, artifacts, and next_recommended.
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 · 23 lines · 14 tokens per session scan A ccea0f2aa2b3
gentle-sdd-init is a command published in the GitHub repository Gentleman-Programming/gentle-ai (6,416 stars, last pushed today), licensed MIT. It adds 14 tokens to every session and 312 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to sdd-init, differing in 26 lines, and is treated as a copy.
Other commands, from other repositories
cross-critique
Adversarial multi-angle critique. All three auditors fire in parallel (codex=technical, gemini=strategic, claude=ux). Counter-args ranked by rebuttal survival score, not raw severity. Usage: /cross-critique [--with | list | compare].
cross-audit
Second-model review. Picks an auditor (codex/gemini/opencode/aider/copilot), excludes the caller, writes a prompt to paste, reads the response back. Usage: /cross-audit [--with | list | compare].
make
Refresh, reconfigure, or extend the project's harness at /.claude/. Asks the user what they want to do before invoking the CLI.
pr-feedback-ingest
Turn PR feedback (Greptile, CI, bots, humans) into a structured traceable backlog aligned with TASKSTATE.md, DECISIONS.md, and IMPLEMENTATIONPLAN.md so the next execution step can be a narrow implement-approved-slice or a small planning touch without losing alignment. Corrective scope only. Use when a PR is open or…
repo-consistency-sweep
Proactive defect-class detection that handles the lower-value half of code review (per Bacchelli and Bird 2013) so human reviewers stay focused on design, intent, and knowledge transfer. Catches convention drift, ordering bugs, type-safety gaps, security and multi-tenant invariants (CWE-grounded), and operability…
code-review
Run parallel specialized review agents and produce aggregated quality report.