Skill: sebclawops/retrospective-agent (version 1.0.0)

--- name: retrospective-agent description: Structured retrospectives and execution-memory hygiene for OpenClaw agents. Use when the user wants a retrospective, lessons learned, self-improvement system, correction logging, weekly review, or a clean way to capture reusable execution lessons without creating hidden memory or autonomous behavior. --- # Retrospective Agent Use this skill to capture execution lessons in a controlled, auditable way. This skill exists to improve how the agent works over time. It does not create a second factual memory system, rewrite identity, or invent autonomy. ## Core principles - Keep factual continuity in existing memory files - Keep execution lessons separate and scoped - Prefer reports and recommendations over automatic changes - Promote patterns only after repeated evidence - Never infer preferences from silence - Never rewrite persona, config, or outbound behavior on your own ## Memory split ### Use existing memory for - facts - events - decisions - dates - people - open tasks Examples: - `memory/YYYY-MM-DD.md` - agent `MEMORY.md` - project `README.md` ### Use retrospective-agent files for - repeated corrections - workflow improvements - tool failure patterns - success patterns worth repeating - project or domain execution lessons ## Storage Skill files live in: - [REDACTED_SECRET] Operational data lives in: - [REDACTED_SECRET] Expected first-pass files: - `workspace/ops/retrospective-agent/corrections.md` - [REDACTED_SECRET] - [REDACTED_SECRET] - [REDACTED_SECRET] - [REDACTED_SECRET] If the ops folder or expected files do not exist, create only the minimum needed for the current task. Do not create extra files "just in case". ## Triggers Use this skill when: - the user asks for a retrospective or lessons learned - a multi-step task ends and a short retro would be useful - the user gives a reusable correction - a process or tool fails in a reusable way - a project needs scoped lessons for future work - a weekly review is requested Do not use this skill for: - one-off instructions with no reusable lesson - customer messaging drafts - sensitive personal profiling - fake automation or hidden monitoring claims ## Operating modes ### 1. Post-task retrospective Use after meaningful work. Output: - what went well - what went wrong - what to repeat - what to change next time - whether anything deserves logging Keep it short and operational. ### 2. Correction logging Use when an explicit correction reveals a reusable lesson. Workflow: 1. capture the exact correction 2. classify it 3. choose scope: project, domain, or global execution lesson 4. append a concise entry if warranted 5. recommend promotion only after repeated evidence ### 3. Weekly retrospective Use on demand or when a scheduled review is explicitly requested. Output: - recurring wins - recurring misses - repeated patterns - candidate updates to memory, README files, or skills ## Scope hierarchy Most specific wins: 1. project 2. domain 3. global execution lesson If scope is unclear, prefer domain over global. If still unclear, say so. ## Promotion model Use conservative states: - observed - repeated - candidate rule - confirmed rule Suggested threshold: - 1 occurrence: observed - 2 occurrences: repeated - 3 occurrences: candidate rule Do not silently promote a candidate into durable agent behavior everywhere. Recommend the promotion and ask when confirmation matters. ## Guardrails Never: - rewrite `SOUL.md` - rewrite `IDENTITY.md` - rewrite `USER.md` - patch config - send messages - install companion skills without approval - infer preferences from silence - store credentials, secrets, or sensitive personal data - claim autonomous monitoring unless a real scheduler exists ## Workflow references Read these only when needed: - `references/workflow.md` - `references/promotion-rules.md` - `references/boundaries.md` Use templates from: - `assets/templates/post-task-retro.md` - `assets/templates/weekly-retro.md` - `assets/templates/lesson-entry.md` ## Style Be honest, compact, and boring in a good way. Avoid AGI theater, inflated claims, and vague self-improvement language. Prefer operational wording like "lesson", "pattern", "correction", and "recommended update" over dramatic wording like "optimize myself" or "evolve". ## Output rule Lead with the useful retrospective or lesson. Do not narrate the framework unless the user asks.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)