hatch3r-context-health

Solid

Monitors and maintains conversation context health during long sessions. Use when context may be degrading, after many turns, or when experiencing repeated errors.

AI & Automation 26 stars 4 forks Updated 1 weeks ago MIT

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Quality Score: 83/100

Stars 20%
48
Recency 20%
90
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# Context Health Monitoring ## Quick Start ``` Task Progress: - [ ] Step 0: Detect ambiguity (P8 B1) - [ ] Step 1: Assess current context health - [ ] Step 2: Identify degradation signals - [ ] Step 3: Apply corrective action - [ ] Step 4: Verify health improvement ``` ## Step 0 — Detect Ambiguity (P8 B1) Before any work, scan the invocation for unresolved questions in scope, intent, acceptance criteria, target environment, or irreversibility. If any are found, ask the user via the platform-native question tool per `agents/shared/user-question-protocol.md`. Do not proceed under silent assumption. Default path, not an exception. Triggers for THIS skill: original task recall, corrective action authority at Orange/Red (delegate vs checkpoint-and-stop), scope of files to re-read, whether to post progress to platform on Red, and irreversible stop (discard unsaved work) vs preserve. ## Fan-out Discipline (P8 B2) Fan-out scales with task size; token cost never justifies serializing independent work (`rules/hatch3r-fan-out-discipline.md` P8 B2; `agents/shared/efficiency-patterns.md`). Emit `sub_agents_spawned: { count, rationale, task_structure }` in your output. ## Step 1: Assess Context Health Run through the self-assessment checklist: 1. **Task recall**: Can you state the original task, acceptance criteria, and scope boundaries without looking? 2. **Progress tracking**: List what's been completed and what remains. 3. **Error check**: Count recent failed tool calls or inco...

Details

Author
hatch3r
Repository
hatch3r/hatch3r
Created
5 months ago
Last Updated
1 weeks ago
Language
TypeScript
License
MIT

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