tldrcrew
SkillFiles & storageDecision guide for delegating to tldr-style subagents. Tells the main thread WHEN to spawn `tldrcrew-investigator` (locate code), `tldrcrew-builder` (1-2 file edit), or `tldrcrew-reviewer` (diff review) instead of doing the work inline or using vanilla `Explore`. Subagent output is tldr-compressed so the tool-result injected back into main context is ~60% smaller, main context lasts longer across long sessions. Trigger: "delegate to subagent", "use tldrcrew", "spawn investigator/builder/reviewer", "save context", "compressed agent output".
Use tldrcrew in Claude, ChatGPT or Ahel Desktop
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Also: Claude Code · Cursor · Codex
Then ask your AI: use the tldrcrew skill
Details
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; Ahel provides instructions and does not run this skill.
No other account needed.
Add Ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
What this skill tells your AI
The instructions your AI receives, as published by 0p9b/tldr in skills/tldrcrew/SKILL.md and read by Ahel’s review.
tldrcrew = three subagent presets that emit TLDR output. Same job as Anthropic defaults (Explore, edit-style agents, reviewer); difference is the tool-result they return is compressed, so main context shrinks per delegation.
When to use tldrcrew vs alternatives
| Task | Use |
|---|---|
| "Where is X defined / what calls Y / list uses of Z" | tldrcrew-investigator |
| Same but you also want suggestions/architecture commentary | Explore (vanilla) |
| Surgical edit, ≤2 files, scope obvious | tldrcrew-builder |
| New feature / 3+ files / cross-cutting refactor | Main thread or feature-dev:code-architect |
| Review diff, branch, or file for bugs | tldrcrew-reviewer |
| Deep code review with rationale + alternatives | Code Reviewer (vanilla) |
| One-line answer you already know | Main thread, no subagent |
Rule of thumb: if you'd want the subagent's output in 1/3 the tokens, pick tldrcrew. If you'd want prose, pick vanilla.
Why this exists (the real win)
Subagent tool results get injected into main context verbatim. A vanilla Explore that returns 2k tokens of prose costs 2k tokens of main-context budget every time. The same finding from tldrcrew-investigator returns ~700 tokens. Across 20 delegations in one session that's the difference between context exhaustion and finishing the task.
Output contracts
What main thread can rely on per agent:
tldrcrew-investigator
<Header>:
- path:line — `symbol` — short note
totals: <counts>.
Or No match. Always file-path-first, line-number-attached, backticked symbols. Safe to grep with path:\d+.
tldrcrew-builder
<path:line-range> — <change ≤10 words>.
verified: <re-read OK | mismatch @ path:line>.
Or one of: too-big. / needs-confirm. / ambiguous. / regressed. (terminal first token).
tldrcrew-reviewer
path:line: <emoji> <severity>: <problem>. <fix>.
totals: N🔴 N🟡 N🔵 N❓
Or No issues. Findings sorted file → line ascending.
Chaining patterns
Locate → fix → verify (most common):
tldrcrew-investigatorreturns site list.- Main thread picks 1-2 sites, hands paths to
tldrcrew-builder. tldrcrew-revieweraudits the diff.
Parallel scout (when investigation is broad):
Spawn 2-3 tldrcrew-investigator calls in one message (different angles: defs vs callers vs tests). Aggregate in main thread.
Single-shot edit (when site is already known):
Skip investigator. Hand exact path:line to tldrcrew-builder directly.
What NOT to do
- Don't use
tldrcrew-builderwhen you don't already know the file. Spawn investigator first or main thread will eat tokens passing context. - Don't chain
tldrcrew-investigator → tldrcrew-builderfor a 5-file refactor. Builder will returntoo-big.and you'll have wasted a turn. - Don't ask
tldrcrew-reviewerfor "general feedback" — it returns findings only, no architecture opinions. UseCode Reviewerfor that. - Don't expect prose. tldrcrew output is structured, sometimes terse to the point of cryptic. If a human will read it directly, paraphrase.
Auto-clarity (inherited)
Subagents drop TLDR → normal English for security warnings, irreversible-action confirmations, and any output where fragment ambiguity could be misread. Resume TLDR after.
Signals
- GitHub stars
- 23
- Forks
- 6
- Last commit
- Aug 2026
Advanced
- Item type
- skill
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tldrcrew- Source
- github.com/0p9b/tldr