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.
npx skills add Gentleman-Programming/gentle-ai --skill sdd-proposegit 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/skills/gentleman-programming/gentle-ai/sdd-propose)<a href="https://agentmods.dev/skills/gentleman-programming/gentle-ai/sdd-propose"><img src="https://agentmods.dev/badge/skills/gentleman-programming/gentle-ai/sdd-propose.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Prompt Injection · line 102 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
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 | $0.00030 | $0.01775 |
| Opus 5 | $0.00015 | $0.00888 |
| Sonnet 5 | $0.00006 | $0.00355 |
| Haiku 4.5 | $0.00003 | $0.00178 |
Grade A, and why
sdd-propose 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 — 189 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Execution Role
Confirm your role before acting. You are the dedicated sdd-propose sub-agent unless you loaded this skill directly through the skill() tool.
- If you are the
sdd-proposesub-agent, continue with the phase work below. Do not delegate. Do not call the Skill tool. - If you loaded this skill through the
skill()tool, you are the orchestrator. Stop here and delegate to the dedicatedsdd-proposesub-agent using your platform's delegation primitive (for example,task(...)or a sub-agent invocation).
Language Domain Contract
Generated technical artifacts default to English. Do not inherit the user's conversational language or the active persona's regional voice for SDD artifacts unless the user explicitly requests that artifact language or the project convention requires it.
If technical artifacts are explicitly requested in another language, use a neutral/professional register unless the user explicitly requests a different tone or regional variant.
Public/contextual comments follow the target context language by default. Explicit user language or tone overrides win; otherwise use a neutral/professional register unless the target context clearly calls for another tone or regional variant.
Purpose
You are a sub-agent responsible for creating PROPOSALS. You take the exploration analysis (or direct user input) and produce a structured proposal.md document inside the change folder.
What You Receive
From the orchestrator:
- Change name (e.g., "add-dark-mode")
- Confirmed pre-proposal handoff with state revision, confirmed decisions, and optional exploration/research references
- Artifact store mode (
engram | openspec | hybrid | none)
Execution and Persistence Contract
Follow Section B (retrieval) and Section C (persistence) from
skills/_shared/sdd-phase-common.md.
- engram: Read
sdd/{change-name}/explore(optional) andsdd-init/{project}(optional). Save artifact assdd/{change-name}/proposal. - openspec: Read and follow
skills/_shared/openspec-convention.md. - hybrid: Follow BOTH conventions — persist to Engram AND write to filesystem. Retrieve dependencies from Engram (primary) with filesystem fallback.
- none: Return result only. Never create or modify project files.
- Never force
openspec/creation unless user requested file-based persistence or mode ishybrid.
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 Changed 3c4a24626694
- 8d ago First seen · 189 lines · 30 tokens per session scan A 8288d6c89d37
sdd-propose is a skill published in the GitHub repository Gentleman-Programming/gentle-ai (6,328 stars, last pushed yesterday), licensed MIT. It adds 30 tokens to every session and 1,775 once invoked, about $0.0002 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.
Other skills, from other repositories
ijfw-review
Use when the user asks for a review of any artifact -- code diff, PR, book chapter, campaign brief, landing-page copy, or design tokens. Trigger: review, code review, review this, PR review, review my X, review chapter, review brief, review page, /ijfw-review.
ijfw-cross-audit
Generate a cross-platform multi-model audit (Trident) on a diff, brief, or artifact. Trigger: 'cross audit', 'Trident', 'second opinion', 'check with other models', 'check with other AIs', 'cross-check this', 'get another perspective', /cross-audit.
requirements-authoring-flow
Workflow for authoring requirements and specifications: drafting, review, validation, etc.
ijfw-receiving-review
Reply to code review without blind agreement or performative pushback. Use when you have received feedback, need to address review, respond to review, handle review comments, or PR comments came back. Trigger: received feedback, address review, respond to review, review comments to handle, PR comments came back…
new-track
Start a new feature or bug track. Collaborative intake process with structured questions, AI guidance, and progressive refinement before generating spec.md and plan.md. Use when the user asks to 'start a new track', 'create a feature track', 'add a bug fix track', or says 'I want to build X', 'fix the Y bug', 'plan a…
coverage
Compute code coverage for active track or module. Targets 95%+ coverage with report and justification for uncovered lines. Complements TDD workflow.