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-verify)<a href="https://agentmods.dev/commands/gentleman-programming/gentle-ai/gentle-sdd-verify"><img src="https://agentmods.dev/badge/commands/gentleman-programming/gentle-ai/gentle-sdd-verify/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/gentleman-programming/gentle-ai/gentle-sdd-verify"><img src="https://agentmods.dev/badge/commands/gentleman-programming/gentle-ai/gentle-sdd-verify.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00009 | $0.00716 |
| Opus 5 | $0.00005 | $0.00358 |
| Sonnet 5 | $0.00002 | $0.00143 |
| Haiku 4.5 | $0.00001 | $0.00072 |
Grade A, and why
gentle-sdd-verify 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 7d 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-verify — 49 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-verify sub-agent is available, delegate this command to it.
Otherwise, read the skill file at ~/.claude/skills/sdd-verify/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: Verify the active SDD change. Read the proposal, specs, design, and tasks artifacts. Then:
This is the single independent requirements/runtime final verification — it runs directly with no review-state prerequisite. A contradiction or failing check escalates; it never launches another review/refuter/fix loop. After verify returns, rerun native SDD status and route only from its refreshed nextRecommended. Present the post-verify review offer only if that refreshed status contains a fresh reviewOffer block; if it is absent, proceed toward archive with no review ceremony — do not call gentle-ai review status and do not fabricate an offer.
STATUS GATE:
Read ~/.claude/skills/_shared/sdd-status-contract.md and produce structured status before acting. If $ARGUMENTS is missing or ambiguous, ask the user to choose and STOP. Do not guess. Continue only when tasks and implementation evidence exist. If status reports workspace-planning, STOP and explain that full workspace implementation verification is not supported in this slice. Carry contextFiles, task progress, dependency states, and actionContext into the native sub-agent prompt when delegating.
ENGRAM PERSISTENCE (artifact store mode: engram): CRITICAL: mem_search returns 300-char PREVIEWS, not full content. You MUST call mem_get_observation(id) for EVERY artifact. STEP A — SEARCH (get IDs only): mem_search(query: "sdd/{change-name}/spec", project: "{project}") → save spec_id mem_search(query: "sdd/{change-name}/design", project: "{project}") → save design_id mem_search(query: "sdd/{change-name}/tasks", project: "{project}") → save tasks_id STEP B — RETRIEVE FULL CONTENT (mandatory): mem_get_observation(id: spec_id) → full spec mem_get_observation(id: design_id) → full design mem_get_observation(id: tasks_id) → full tasks Save report: mem_save(title: "sdd/{change-name}/verify-report", topic_key: "sdd/{change-name}/verify-report", type: "architecture", project: "{project}", capture_prompt: false, content: "{verification report}") 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.
Then:
- Check completeness — are all tasks done?
- Check correctness — does code match specs?
- Check coherence — were design decisions followed?
- Run tests and build (real execution)
- Build the spec compliance matrix
Return a structured verification report with: status, executive_summary, detailed_report, 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.
- 7d ago First seen · 43 lines · 9 tokens per session scan A 2f32af968c35
gentle-sdd-verify is a command published in the GitHub repository Gentleman-Programming/gentle-ai (6,416 stars, last pushed yesterday), licensed MIT. It adds 9 tokens to every session and 716 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to sdd-verify, differing in 49 lines, and is treated as a copy.
Other commands, from other repositories
testgen-flow-test-case-generation
Phase 5 Test Case Generation of testgen-flow.
api-aqa-flow-project-config-loading
Phase 0 Project Config Loading of api-aqa-flow (USER INTERACTION CONDITIONALLY REQUIRED).
testgen-flow-project-config-loading
Phase 0 Project Config Loading of testgen-flow.
testgen-flow-question-generation
Phase 3 Question Generation of testgen-flow.
testgen-flow-test-case-export
Phase 6 Test Case Export of testgen-flow.
testgen-flow-data-collection
Phase 1 Data Collection of testgen-flow.