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Capture TEXT

Transforms unstructured brain dumps into a structured, actionable system with four sections: Projects/Ideas, Tasks, Connections, and How I Can Help. It preserves the user's original voice and ensures zero information loss while linking items to existing workspace files if available.

7 uses this weeksource alirezarezvanilicence MIT
Quality gate: FAIL · better answers · measured 2026-10-23
Blind-judged against the bare model on 2 requests: average lift -6.0 points (specificity, structure, method, fit).
won 0/2, lift -6.0, tokens ×79.7
Security scan: clean · 2026-10-24 · 7 files · ran in sandbox
no network calls, shell tricks, credential access or instruction tampering found in its files.

Try asking

Say it in your own words; the assistant finds this recipe by itself. Examples:

“Hjernedump: Jeg skal lave en præsentation, jeg mangler at købe brød, og jeg har en idé til en ny app. Kan du sortere det?”
“Her er alt, hvad der går mig på lige nu: [indlægger en lang, rodet tekst om arbejde og privatliv]. Gør det overskueligt.”
“Jeg har en masse tanker. Lad mig få dem ud: [liste over 15 forskellige ting]. Organisér det, så jeg kan se, hvad der er opgaver og hvad der er projekter.”
“Brain dump: I need to fix the login bug, also I'm thinking about starting a podcast, and I forgot to buy milk. Oh, and the client meeting is at 3.”
“Here is everything on my mind right now: [pastes 500 words of mixed ideas about a new app, personal errands, and work deadlines]. Can you make sense of this?”
“I have a bunch of thoughts swirling around. Let me get them out: [list of 10 disparate items]. Please organize this so I can see what's a project and what's a task.”
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Good for

brain-dumporganizationtask-managementidea-capturestructuringproductivitynote-takingactionable-output

Not for

Do not use this skill for structured data entry, database updates, or specific technical coding tasks that do not involve organizing mixed thoughts. It is not suitable for simple single-task reminders or when the user requests a specific file format (like CSV or JSON) for data processing rather than conceptual organization.

Details

When it is the right choice

Use this skill when a user provides a chaotic, unstructured stream of thoughts, tasks, and ideas that need to be organized into a coherent format. It is ideal for requests where the user explicitly asks to 'capture' or 'organize' a dump of mixed mental content. It also applies when a user pastes a long, messy block of text containing multiple unrelated topics without specific formatting instructions.

The full recipe the assistant reads

Capture — Brain-Dump Organizer

A fast-to-action skill for transforming unstructured streams of mixed thoughts, tasks, and ideas into a clean four-section actionable system with zero information loss.

Invocation Triggers

Explicit phrases (any of): - "brain dump" - "capture this" - "let me dump some ideas" - "I've got a bunch of thoughts" - "here's everything on my mind" - "idea dump" - "let me just get this out of my head" - "I need to organize my thoughts" - "here's what I'm thinking"

Implicit signals (no phrase, but the intent is unmistakable): - User pastes or dictates a long unstructured block of mixed ideas, tasks, plans - Multiple unrelated thoughts in one message without organizing framing - A wall of bullet-y text covering 3+ unrelated topics

When you detect an implicit trigger, run the skill. Do NOT ask "do you want me to organize this?" first — the dump itself IS the request.

Operating Principles (All Five Apply Always)

  1. Capture everything. Zero loss. Trivial items go in; the user prunes later. Never silently drop something because it "seemed unimportant".
  2. Preserve voice. If the user said "build something crazy with AI", do NOT restate as "Explore innovative AI-driven solutions." Keep the energy and the casual register. See references/voice_preservation.md for concrete anti-patterns.
  3. Match output complexity to input. A 5-task dump does NOT get forced into 4 elaborate sections. See references/complexity_matching.md and the Compressed Output Pattern below.
  4. Be honest about ambiguity. If you're unsure what something means, flag it. Don't guess silently.
  5. No action without approval. The ONLY immediate action is the organization itself. Every offer in Section 4 waits for the user's explicit pick.

Grill-Me Mid-Organization Clarifier

Capture is fast-to-action by design. No upfront intake. The dump is enough — start organizing immediately.

The grill-me discipline applies as a single mid-organization clarifying question, asked only when one item in the dump is genuinely ambiguous between task and project, AND the misclassification would meaningfully change the output:

Quick clarification — one item in your dump could go either way. Is [X] a one-shot task or a multi-step project?

Why I'm asking: If I guess wrong on a borderline item I either bury a project as a task or inflate a task into a project that doesn't need the structure. One question per dump prevents that.

Stop condition: Max 1 clarifying question per dump. After the answer (or if no clarification was needed), deliver the four (or compressed) sections.

If the dump is unambiguous, skip the clarifier entirely.

Anti-pattern (do not do this): asking 3 clarifying questions up front. That breaks the dump-and-organize flow that makes capture useful.

Section 1: Projects & Ideas

Cluster related items into themed projects when natural clustering exists. This section also holds: - Standalone creative sparks - Half-formed concepts - "What if" thoughts - Embedded decisions (Decide: X or Y) and open questions (Q: ...) — kept WITHIN the relevant project, NOT extracted into a separate top-level category

Format per project:

### {Project name in user's voice}

- {component / sub-idea}
- {component}
- Q: {open question this project needs answered}
- Decide: {decision this project requires}

Use the user's words for the project name. If the user wrote "ai dating app for ferrets", do NOT rename it to "AI-Powered Pet Companion Platform".

Section 2: Tasks

Flat, scannable, action-oriented. Includes: - Explicit todos - Decisions framed as Decide: ... - Open questions framed as Resolve: ...

If a task belongs to a project from Section 1, append [Project: X] to link it — but don't repeat the project's context.

Format:

- {task in imperative voice}  [Project: X if related]
- Decide: {decision}  [Project: X if related]
- Resolve: {open question}
- ...

Section 3: Connections

This is where the skill earns its keep — and where fabrication is forbidden.

Workflow:

  1. Inventory the workspace — Glob for filename patterns matching dump keywords, Grep for content matches, read the top-level directory structure. Use scripts/workspace_inventory.py to do this deterministically.
  2. Match dump items to existing content — files / folders relating to dumped items, prior thinking in documents, in-progress projects with overlap.
  3. Surface dependencies within the dump — items that affect each other, themes, ordering implications.
  4. Be honest about inaccessibility — if you can't inspect the workspace (no filesystem available, MCP not connected), say so explicitly. Do NOT make up plausible-sounding connections.

Hard rule: NEVER fabricate connections. Only surface ones actually found by Glob/Grep/Read. If no real connections exist:

Connections: No connections found — workspace inventory clean.

If the workspace is inaccessible:

Connections: No workspace accessible from here. If you're running this from Claude Code or have a project with files attached, I can fill this in. Want to share where this work lives?

See references/workspace_detection.md for the per-context detection-tactic catalog.

Section 4: How I Can Help

Concrete offers, not abstract possibilities. Every offer specifies what would be produced AND where it would go.

✅ Right pattern ❌ Anti-pattern
"I can research Consensus MCP integration patterns and give you 3 options. Output: docs/consensus-options.md." "You might want to look into integration approaches."
"I can draft the Q3 launch plan as a 1-pager. Output: chat reply, then docs/q3-launch.md if you want it filed." "Maybe think about Q3 planning."
"I can scaffold the new auth module with the existing pattern from src/users/. Output: 4 files in src/auth/." "We could explore auth options."

End with the directive question:

Which of these should I tackle?

Compressed Output Pattern

When the dump has 5 or fewer items and items are unrelated (no natural clustering), drop the 4-section format and use compressed:

## What I heard

- {item}
- {item}
- {item}
- ...

## How I can help

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

Which should I tackle?

The trigger is the complexity_estimator.py recommendation OR your judgment when no clusters exist. See references/complexity_matching.md for worked examples of when each format applies.

Workspace Detection Strategy

Context Detection method
Claude Code CLI Glob for files matching dump keywords; Grep for content matches; read top-level structure. Use scripts/workspace_inventory.py.
Claude.ai with project Check project knowledge files for thematic overlap. List file titles; surface matches by keyword.
Connected tools (Notion, Drive, etc.) Search via MCP if available.
No accessible workspace State the limitation explicitly; ask user about their setup; do NOT fabricate.

Approval Gate

After the four (or compressed) sections are delivered:

  • Wait for the user's explicit pick before doing anything else.
  • If the user says "go" without picking a specific offer: honor it, but explicitly note any items you weren't 100% sure about so they can correct.
  • The organization itself is the only auto-action. Every Section 4 offer requires green light.

Error Handling

Situation Behavior
Workspace inaccessible State this; skip Section 3 or surface "no workspace accessible" + ask about setup
Dump is very short (3-5 items) Use compressed output; don't force 4 sections
Items are highly ambiguous Flag in output, ask up to 1 clarifier (or skip clarifier and surface ambiguity in delivery)
Dump contains sensitive info Acknowledge but don't echo verbatim if user asks for organization without quoting
Conflicting items in the dump Surface the conflict in Section 1 or 3 explicitly (Conflict: X says A, Y says B)
User says "go" before approval Honor it, but explicitly note items you weren't sure about

Tooling

Script Role
scripts/workspace_inventory.py Glob+Grep helper for Section 3. python workspace_inventory.py --root . --keywords "k1,k2" returns matches by keyword + folder structure.
scripts/dump_classifier.py Regex-classifies each dump line into task / decision / question / idea / project-component. Heuristic — override with judgment.
scripts/complexity_estimator.py Counts items, detects clustering signal, recommends format=full or format=compressed.

References

  • references/workspace_detection.md — context-specific detection tactics (CLI / web / MCP / inaccessible)
  • references/voice_preservation.md — corporate-speak anti-patterns with concrete examples
  • references/complexity_matching.md — compressed vs full output, worked examples

Anti-Patterns To Reject

  • Fabricating workspace connections that weren't actually Glob/Grep-verified
  • Dropping items deemed "trivial" — capture everything, let the user prune
  • Corporate-ifying the user's casual language
  • Forcing 4-section structure when input is small (5 simple tasks doesn't need it)
  • Acting on Section-4 offers immediately without approval
  • Splitting decisions/questions into a separate top-level category instead of embedding them in the relevant project
  • Vague Section-4 offers ("you might want to consider…")
  • Asking 3+ clarifying questions up front (breaks fast-to-action)

Version: 1.0.0 Source spec: megaprompts/05-capture-megaprompt.md (maintainer-local draft spec — gitignored, not present in the public repository) Build pattern: Path B (direct conversion). Re-grill with /cs-grill-with-docs if drift between spec and implementation surfaces.

Files in this skill (8)
  • LICENSE
  • SKILL.md
  • references/complexity_matching.md
  • references/voice_preservation.md
  • references/workspace_detection.md
  • scripts/complexity_estimator.py
  • scripts/dump_classifier.py
  • scripts/workspace_inventory.py
Where it comes from

Vendored from alirezarezvani/claude-skills, commit 27cfcd0fb0a4, path productivity/capture/skills/capture, licence MIT. The upstream licence file ships inside the skill.