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 agentmods add commands/gentleman-programming/gentle-ai/sdd-ffgit 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/sdd-ff)<a href="https://agentmods.dev/commands/gentleman-programming/gentle-ai/sdd-ff"><img src="https://agentmods.dev/badge/commands/gentleman-programming/gentle-ai/sdd-ff.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 | $0.00011 | $0.00442 |
| Opus 5 | $0.00005 | $0.00221 |
| Sonnet 5 | $0.00002 | $0.00088 |
| Haiku 4.5 | $0.00001 | $0.00044 |
Grade A, and why
sdd-ff scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Follow the SDD orchestrator workflow to fast-forward all planning phases for change "$ARGUMENTS".
HARD GATE: SDD Session Preflight must already be complete for this session. It must include execution mode, artifact store, chained PR strategy, and review budget. If missing, ask the exact orchestrator preflight prompt and STOP. Do not launch planning sub-agents in the same turn.
WORKFLOW: Honor the cached execution mode from SDD Session Preflight.
Planning phases:
- sdd-propose — create the proposal
- sdd-spec — write specifications
- sdd-design — create technical design
- sdd-tasks — break down into implementation tasks
- In
interactivemode: run only the next planning phase, present its summary and artifact path(s), ask whether to adjust or continue, then STOP. Do not launch the following phase until the user confirms. - In
automode: run all planning phases back-to-back and present a combined summary after all phases complete.
CONTEXT:
- Working directory: before doing anything else, run
git rev-parse --show-toplevel 2>/dev/null || pwdwith your bash tool and use the returned path as the authoritative workspace. In OpenCode Desktop (Electron) the parse-time interpolation resolves to the app data directory, not the project. - Current project: the
basenameof the detected workspace above. - Change name: $ARGUMENTS
- Execution mode: ask/cache per orchestrator
- Artifact store mode: ask/cache per orchestrator; do not hardcode Engram
- Delivery strategy: ask/cache per orchestrator
- Review budget: ask/cache per orchestrator
ENGRAM NOTE: Sub-agents handle persistence automatically using the selected artifact store. In engram/hybrid, each phase saves with topic_key "sdd/$ARGUMENTS/{type}" where type is: proposal, spec, design, tasks.
Read the orchestrator instructions to coordinate this workflow. Do NOT execute phase work inline — delegate to sub-agents.
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.
- 3d ago Changed · +4 lines ef7c59826ac2
- 5d ago First seen · 34 lines · 11 tokens per session scan A 17a12f15a0d7
sdd-ff is a command published in the GitHub repository Gentleman-Programming/gentle-ai (6,255 stars, last pushed today), licensed MIT. It adds 11 tokens to every session and 442 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.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.