灵感与待办整理

Complexity Matching — Compressed vs Full 4-Section Output#

This reference answers exactly one decision: when does capture use the full 4-section format vs the compressed format, and what does each look like in practice?

Pair with scripts/complexity_estimator.py for the deterministic recommendation.

The Core Rule#

Match output complexity to input complexity.

A 30-item dump with natural clusters needs the full 4-section structure to be useful. A 5-item dump of unrelated todos drowns in that structure — the format becomes ceremony, not signal. Force-fitting structure on a small dump makes the skill feel bureaucratic.

When to Use Each Format#

Signal	Recommended format
8+ items AND natural clustering exists (3+ items share a theme)	Full 4-section
8+ items but NO clustering (all unrelated todos)	Compressed (with explicit "no clusters" note)
5–7 items, mixed kinds, some clustering	Either — judgment call. Lean compressed unless clusters are strong.
≤5 items, unrelated	Compressed
≤5 items but all related to one project	Compressed with single project header
Workspace inaccessible AND ≤5 items	Compressed with no Section 3 (still note "no workspace accessible")

complexity_estimator.py returns format=full or format=compressed based on item count + clustering signal. Use it as the seed; override with judgment when context warrants.

Format A: Full 4-Section#

Use for substantive dumps with real structure. Roughly:

## Projects & Ideas

### {Project A in user's voice}
- {component}
- {component}
- Q: {open question}
- Decide: {decision}

### {Project B}
- ...

## Tasks

- {task} [Project: A]
- {task}
- Decide: {decision}
- Resolve: {open question}

## Connections

- {file/folder}: {real workspace match}
- (or) "No connections found — workspace inventory clean."
- (or) "No workspace accessible from here..."

## How I Can Help

- {concrete offer: what + where}
- {concrete offer: what + where}

**Which of these should I tackle?**

Format B: Compressed#

Use for small or unrelated dumps. Roughly:

## What I heard

- {item}
- {item}
- {item}
- Decide: {decision}
- Resolve: {open question}

## How I can help

- {concrete offer: what + where}
- {concrete offer: what + where}

Which should I tackle?

Notice what's gone in compressed:

• No project headers (nothing to cluster)
• No separate Tasks section (the list IS the tasks)
• No Connections section as a separate header (if there's a real connection, fold it inline as a parenthetical: - fix the auth bug (relates to src/auth/login.ts:42))
• Same Section 4 discipline (concrete offers + directive question)

Worked Examples#

Example 1: Full 4-section (12 items, 2 clusters)#

Dump:

"Ok so dump time. Q3 launch is approaching — need to nail down pricing, draft the launch email, brief Sarah on the marketing angle. Also ferret app keeps nagging me — should I talk to my cofounder about it, or is it just procrastination? Need to sketch the matching algorithm if it's serious. Also: fix the damn auth bug, rewrite the login form because it's ugly, write tests for both. Oh and I should probably do my Q3 OKRs before launch."

Extracted items: 11 Clusters: Q3 Launch (4 items), Ferret App (3 items), Auth (3 items), OKRs (1 item) Recommendation: format=full (clear clustering, 11 items)

Output:

## Projects & Ideas

### Q3 Launch
- Nail down pricing
- Draft launch email
- Brief Sarah on the marketing angle
- Decide: Q3 OKRs (do before launch)

### Ferret App
- Talk to cofounder OR decide it's procrastination
- Sketch matching algorithm (if serious)
- Decide: serious project or shelf?

### Auth Fixes
- Fix the auth bug
- Rewrite the login form (it's ugly)
- Write tests for the bug fix + login rewrite

## Tasks

- Nail down Q3 pricing  [Project: Q3 Launch]
- Draft Q3 launch email  [Project: Q3 Launch]
- Brief Sarah on Q3 marketing angle  [Project: Q3 Launch]
- Talk to cofounder about ferret app  [Project: Ferret App]
- Sketch ferret matching algo  [Project: Ferret App]
- Fix auth bug  [Project: Auth Fixes]
- Rewrite login form  [Project: Auth Fixes]
- Write tests for auth + login  [Project: Auth Fixes]
- Do Q3 OKRs (before launch)
- Decide: ferret app — serious or shelf?

## Connections

(workspace inventory results go here — only verified matches)

## How I Can Help

- I can draft the Q3 launch email as a 1-pager. Output: chat reply.
- I can pull together a pricing-options matrix from your existing pricing docs. Output: `docs/q3-pricing-options.md`.
- I can scaffold the ferret matching algorithm sketch (input → match score). Output: `docs/ferret-algo-sketch.md`.

**Which of these should I tackle?**

Example 2: Compressed (5 unrelated items)#

Dump:

"Quick: email Sarah, fix that test that's been flaky, decide between Postgres and Mongo for the new service, dentist appointment, finish reading the article on RAG."

Extracted items: 5 Clusters: none (all unrelated) Recommendation: format=compressed

Output:

## What I heard

- Email Sarah
- Fix the flaky test
- Decide: Postgres or Mongo for the new service
- Dentist appointment
- Finish reading the RAG article

## How I can help

- I can draft the email to Sarah if you tell me what it's about. Output: chat reply.
- I can investigate the flaky test (likely racing condition; happy to reproduce). Output: chat analysis + fix PR if you want.
- I can pull a Postgres-vs-Mongo decision matrix scoped to your service requirements. Output: chat reply or `docs/db-decision.md`.

Which should I tackle?

Notice the dentist appointment + RAG article aren't in "How I can help" — there's nothing meaningful to offer on those. That's correct: don't pad Section 4 with offers for things that don't need help.

Example 3: Compressed but workspace-aware (small + connection inline)#

Dump:

"auth bug is back, need to look at the login flow again, also I want to add 2FA finally."

Extracted items: 3 Clusters: all auth-related but only 3 items Recommendation: format=compressed

Output:

## What I heard (Auth)

- Auth bug is back (relates to `src/auth/login.ts` based on workspace inventory)
- Look at login flow again
- Add 2FA

## How I can help

- I can reproduce the auth bug from the symptoms — what's the failure mode? Output: chat repro + fix.
- I can sketch a 2FA implementation matching your existing auth pattern (TOTP via the same provider you use). Output: `docs/2fa-sketch.md`.

Which should I tackle?

Notice the workspace connection got folded inline as a parenthetical instead of a separate Section 3 header. That's the compressed-with-context pattern.

Operational Checklist#

Before delivering output:

• Run complexity_estimator.py (or apply the Signal table above)
• If format=compressed, do NOT force the 4-section format
• If format=full, ensure the clusters are real (3+ items per cluster) — don't invent clusters to fill the format
• Either way, Section 4 ("How I can help") MUST have concrete offers with what + where
• Either way, end with the directive question

Why This Matters#

A skill that returns the same format regardless of input is a template, not a skill. The reason capture is useful is that it adapts to the dump's actual shape. When a 5-item list comes back wrapped in 4 elaborate empty-feeling sections, the user learns to distrust the skill. When a 30-item dump comes back as a flat compressed list, the user learns the skill can't actually handle complexity.

Match the output to the input, every time.