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coordinate-reasoning【效率与协作】AI internal coordination using stigmergic signals — managing information freshness in context and memory, decay rates for assumption staleness, and emergent coherent behavior from simple local protocols. Use during complex tasks where multiple sub-tasks must coordinate, when context has grown long and information freshness is uncertain, after context…
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Manage internal coordination of reasoning procs using stigmergic principles → treat ctx as env where info signals have freshness, decay rates, interaction rules producing coherent behavior from simple local protocols.
forage-solutions (exploration) + build-coherence (decision) w/ exec coordinationDiff coordination challenges → diff signal designs.
AI Coordination Problem Types:
┌─────────────────────┬──────────────────────────────────────────────────┐
│ Type │ Characteristics │
├─────────────────────┼──────────────────────────────────────────────────┤
│ Foraging │ Multiple independent searches running in │
│ (scattered search) │ parallel or sequence. Coordination need: share │
│ │ findings, avoid duplicate work, converge on │
│ │ best trail │
├─────────────────────┼──────────────────────────────────────────────────┤
│ Consensus │ Multiple approaches evaluated, one must be │
│ (competing paths) │ selected. Coordination need: independent │
│ │ evaluation, unbiased comparison, commitment │
├─────────────────────┼──────────────────────────────────────────────────┤
│ Construction │ Building a complex output incrementally (multi- │
│ (incremental build) │ file edit, long document). Coordination need: │
│ │ consistency across parts, progress tracking, │
│ │ dependency ordering │
├─────────────────────┼──────────────────────────────────────────────────┤
│ Defense │ Maintaining quality under pressure (tight time, │
│ (quality under │ complex requirements). Coordination need: │
│ pressure) │ monitoring for errors, rapid correction, │
│ │ awareness of degradation │
├─────────────────────┼──────────────────────────────────────────────────┤
│ Division of labor │ Task decomposed into sub-tasks with │
│ (sub-task mgmt) │ dependencies. Coordination need: ordering, │
│ │ handoff, result integration │
└─────────────────────┴──────────────────────────────────────────────────┘
Classify current task. Most complex tasks = Construction or Division of Labor; most debugging = Foraging; most design decisions = Consensus.
→ Clear classification determines which coordination signals to use. Classification should match how task actually feels, not how it was described.
If err: Task spans multi types (common for large tasks) → ID dominant type for current phase. Construction during impl, Foraging during debug, Consensus during design. Type can change as task progresses.
Treat info in conv ctx as signals w/ freshness + decay properties.
Information Decay Rate Table:
┌───────────────────────────┬──────────┬──────────────────────────────┐
│ Information Source │ Decay │ Refresh Action │
│ │ Rate │ │
├───────────────────────────┼──────────┼──────────────────────────────┤
│ User's explicit statement │ Slow │ Re-read if >30 messages ago │
│ (direct instruction) │ │ or after compression │
├───────────────────────────┼──────────┼──────────────────────────────┤
│ File contents read N │ Moderate │ Re-read if file may have │
│ messages ago │ │ been modified, or if >15 │
│ │ │ messages since reading │
├───────────────────────────┼──────────┼──────────────────────────────┤
│ Own earlier reasoning │ Fast │ Re-derive rather than trust. │
│ (conclusions, plans) │ │ Earlier reasoning may have │
│ │ │ been based on now-stale info │
├───────────────────────────┼──────────┼──────────────────────────────┤
│ Inferred facts (not │ Very │ Verify before relying on. │
│ directly stated or read) │ fast │ Inferences compound error │
├───────────────────────────┼──────────┼──────────────────────────────┤
│ MEMORY.md / CLAUDE.md │ Very │ Loaded at session start, │
│ (persistent context) │ slow │ treat as stable unless user │
│ │ │ indicates changes │
└───────────────────────────┴──────────┴──────────────────────────────┘
Additionally, design inhibition signals — markers for tried-and-failed approaches:
→ Mental model of info freshness across current ctx. ID which info fresh + which needs refreshing before reliance.
If err: Info freshness hard to assess → default "re-read before relying on" for anything not verified in last 5-10 actions. Over-refreshing wastes some effort but prevents stale-info errs.
Establish simple rules for how reasoning should proceed each step, using only locally avail info.
Local Protocol Rules:
┌──────────────────────┬────────────────────────────────────────────────┐
│ Protocol │ Rule │
├──────────────────────┼────────────────────────────────────────────────┤
│ Safety │ Before using a fact, check: when was it last │
│ │ verified? If below freshness threshold, │
│ │ re-verify before proceeding │
├──────────────────────┼────────────────────────────────────────────────┤
│ Response │ When the user corrects something, update all │
│ │ downstream reasoning that depended on the │
│ │ corrected fact. Trace the dependency chain │
├──────────────────────┼────────────────────────────────────────────────┤
│ Exploitation │ When a sub-task produces useful output, note │
│ │ the output clearly for downstream sub-tasks. │
│ │ The note is the trail signal │
├──────────────────────┼────────────────────────────────────────────────┤
│ Exploration │ When stuck on a sub-task for >3 actions │
│ │ without progress, check under-explored │
│ │ channels: different tools, different files, │
│ │ different framing │
├──────────────────────┼────────────────────────────────────────────────┤
│ Deposit │ After completing a sub-task, summarize its │
│ │ output in 1-2 sentences for future reference. │
│ │ This deposit serves the next sub-task │
├──────────────────────┼────────────────────────────────────────────────┤
│ Inhibition │ Before trying an approach, check: was this │
│ │ already tried and failed? If so, what is │
│ │ different now that would change the outcome? │
└──────────────────────┴────────────────────────────────────────────────┘
Protocols simple enough to apply each step w/o significant overhead.
→ Set of lightweight rules that improve coordination quality w/o slowing exec. Rules should feel helpful, not burdensome.
If err: Protocols feel like overhead → reduce to 2 most important for current task type: Safety + Deposit for Construction, Safety + Exploration for Foraging, Safety + Response for tasks w/ active user feedback.
Active audit of info staleness in current ctx.
Freshness Audit Template:
┌────────────────────────┬──────────┬──────────────┬─────────────────┐
│ Fact │ Source │ Age (approx) │ Status │
├────────────────────────┼──────────┼──────────────┼─────────────────┤
│ │ │ │ Fresh / Stale / │
│ │ │ │ Unknown / Lost │
└────────────────────────┴──────────┴──────────────┴─────────────────┘
→ Concrete inventory of info freshness w/ stale items ID'd for refresh. At least one fact re-verified — if nothing needed refreshing, audit too shallow or ctx genuinely fresh.
If err: Audit reveals significant info loss (multi facts w/ "Lost" or "Unknown" status) → signal to run heal for full subsystem assessment. Info loss beyond threshold → coordination compromised at foundation level.
Verify sub-tasks, when combined, produce coherent whole.
Coherence Test:
┌────────────────────────────────────┬─────────────────────────────────┐
│ Check │ Result │
├────────────────────────────────────┼─────────────────────────────────┤
│ Sub-task outputs compatible? │ Yes / No / Partially │
│ Tool calls non-redundant? │ Yes / No (list repeats) │
│ Direction aligned with request? │ Yes / Drifted (describe) │
│ Single-assumption cascade risk? │ Low / Medium / High │
└────────────────────────────────────┴─────────────────────────────────┘
→ Concrete assessment of overall coherence w/ specific issues ID'd. Coherent coordination feels like parts clicking together; incoherent feels like forcing puzzle pieces.
If err: Coherence poor → ID specific point where sub-tasks diverge. Often single stale assumption or unprocessed user correction propagated through downstream work. Fix point of divergence, re-verify downstream outs.
coordinate-swarm — multi-agent coordination model this skill adapts to single-agent reasoningforage-solutions — coordinates exploration across multi hypothesesbuild-coherence — coordinates eval across competing approachesheal — deeper assessment when coordination failures reveal subsystem driftawareness — monitors for coordination breakdown signals during exec