capture-observation
SolidAppend a single observation, question, hypothesis, or concern to TASK_STATE.md as task memory without disrupting in-progress work or requiring a full state sync. Lean append-only; never restructures other artifacts. Use when something surfaces mid-work that should be remembered for later (during planning, implementation, or review), when you noticed something not actionable now but should not be lost, when you want to log a hypothesis to validate before closure, or when a small concern does not justify decision-interview or targeted-questions but deserves to be on record. Do not use when the observation is a canonical decision (use decision-interview or sync-task-state), invalidates the current direction (use direction-adjust), requires several artifact changes (use sync-task-state or state-reconcile), or when there is no active task folder yet (run task-init first).
Install
Quality Score: 81/100
Skill Content
Details
- Author
- Mozurok
- Repository
- Mozurok/fhorja.dev
- Created
- 1 months ago
- Last Updated
- 5 days ago
- Language
- Python
- License
- MIT
Similar Skills
Semantically similar based on skill content — not just same category
compact-task-memory
Produce a lossy compaction summary of TASK_STATE.md when task memory has grown beyond a useful working size, preserving canonical decisions and recommended next step while dropping stale facts. Distinct from sync-task-state (incremental, append-only, never lossy) and state-reconcile (drift repair, no shrinking). Use when task memory has accumulated across multiple slices (5+ completed) and feels heavy, the resume cost is growing as the file scales, the current known facts list is full of resolved or routine entries, or before a session pause where a slim TASK_STATE will speed restart. Do not use when the task is still in early discovery (memory is small), the artifacts disagree across files (use state-reconcile first), an incremental sync would be sufficient (use sync-task-state), or no active task folder exists yet (run task-init first).
direction-adjust
Capture a small-to-medium course correction the user realized mid-task (not from external review), record it as a numbered D-N entry in DECISIONS.md, update TASK_STATE.md to reflect the adjusted direction, and route back to the appropriate command. Use when you are mid-task (any phase past discovery) and realize the direction needs adjustment, the realization came from your own work (not external review), the change is meaningful enough to record but does not invalidate the whole approach, and the existing slice or phase is recoverable with a small change of plan. Do not use when the trigger is external review or PR feedback (use pr-feedback-ingest or post-review-pivot), the realization invalidates the entire task scope (use task-init for a new task), the adjustment is too small to record (use capture-observation), the realization is loop or confusion (use im-stuck), the adjustment requires reopening locked decisions (use decision-interview), or no active task folder exists yet.
harvest-session-learnings
Scan the current working session and the active task's artifacts for reusable, generalizable lessons (what was tried, what failed and why, what surprised us, what the next task should do differently) and propose anchored entries to append to the task's LEARNINGS.md, the produce-side counterpart to the ADR-0017 consume path that task-init already reads. Append-only and read-only on existing entries; de-duplicates against what is already captured; keeps durable lessons and drops one-off task trivia. Use on demand mid-task after a hard-won fix or a surprising failure, or at closure to sweep a long session before the context is lost. Do not use to rewrite or prune existing learnings (never edit prior entries), to capture a single in-flight observation (use capture-observation), to close a slice or the task (use slice-closure or task-close), or when nothing durable was learned (return a NO_OP rather than manufacturing a lesson).