speckit-memory
Capture stable lessons from a speckit run into persistent project memory and create/update helper skills when repeated repo-specific workflows emerge.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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Capture stable lessons from a speckit run into persistent project memory and create/update helper skills when repeated repo-specific workflows emerge.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Autonomous end-to-end speckit pipeline: specify → clarify (self-answered) → plan → tasks → implement → open PR. No human input required.
Investigate SonarCloud quality gate failures for the current GitHub pull request. Use when a PR has a failing SonarCloud check, when the user asks where duplication or other Sonar failures come from, or when you need to trace a GitHub Sonar check into SonarCloud file-level and block-level details.
Use when the user wants to work through the automata CLI feature-delivery loop: pick up the next GitHub issue with `automata implement-next`, monitor PR status and CI checks with `automata git get-pr-info`, inspect unresolved review threads with `automata git get-pr-comments`, address reviewer feedback, and finish a merged feature with `automata git finish-feature`. Also use when the user asks how automata works for day-to-day implementation flow in this repository.
| name | speckit-memory |
| description | Capture stable lessons from a speckit run into persistent project memory and create/update helper skills when repeated repo-specific workflows emerge. |
| compatibility | Requires spec-kit project structure with .specify/ directory |
| metadata | {"author":"automata-cli"} |
$ARGUMENTS
Use any user-provided notes as additional context, but do not require them.
Persist reusable lessons from the current speckit-full execution so the next run starts with better repo-specific context and less friction.
Write durable memory to .specify/memory/speckit-memory.md. Create or update a helper skill under .agents/skills/ only when a repeated repo-specific workflow is stable enough to deserve its own instructions.
Record only information that is likely to help future runs:
Do not record:
AGENTS.md, or .specify/memory/constitution.mdResolve the active feature with .specify/scripts/bash/check-prerequisites.sh --json --paths-only.
Read only the artifacts needed to extract durable lessons:
.specify/memory/constitution.mdAGENTS.md.specify/memory/speckit-memory.md if presentspec.md, plan.md, tasks.mdresearch.md, pr-report.md, and spec-decisions.md if presentExtract candidate lessons and classify each one:
keep: stable and reusablepromote: stable enough for a helper skilldrop: too specific, stale, or noisyIf .specify/memory/speckit-memory.md does not exist, create it from .specify/templates/speckit-memory-template.md.
Update the memory file by section:
## Autonomous Defaults## Implementation Patterns## Process Friction## Helper SkillsUse concise bullets in this format:
- **<topic>**: <rule or preferred action>. Why: <short rationale>. Confirmed: <YYYY-MM-DD>.
De-duplicate semantically similar bullets, refresh the Confirmed date for surviving entries, and remove entries that are now contradicted.
Keep the file lean:
Create or update a helper skill only if all of the following are true:
When promoting:
.agents/skills/<skill-name>/SKILL.md.specify/memory/speckit-memory.md only when needed; do not copy large memory sections into the skill## Helper Skills sectionIf a candidate workflow does not meet the bar, keep it as a memory bullet instead of creating a new skill.
Report: