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.
Explicit phrases (any of):
Implicit signals (no phrase, but the intent is unmistakable):
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.
references/voice_preservation.md for concrete anti-patterns.references/complexity_matching.md and the Compressed Output Pattern below.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.
Cluster related items into themed projects when natural clustering exists. This section also holds:
Decide: X or Y) and open questions (Q: ...) — kept WITHIN the relevant project, NOT extracted into a separate top-level categoryFormat 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".
Flat, scannable, action-oriented. Includes:
Decide: ...
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}
- ...
This is where the skill earns its keep — and where fabrication is forbidden.
Workflow:
scripts/workspace_inventory.py to do this deterministically.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.
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?
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.
| 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. |
After the four (or compressed) sections are delivered:
| 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 |
| 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/workspace_detection.md — context-specific detection tactics (CLI / web / MCP / inaccessible)references/voice_preservation.md — corporate-speak anti-patterns with concrete examplesreferences/complexity_matching.md — compressed vs full output, worked examplesVersion: 1.0.0
Source spec: megaprompts/05-capture-megaprompt.md
Build pattern: Path B (direct conversion). Re-grill with /cs:grill-with-docs if drift between spec and implementation surfaces.