deliverable-builder
Skill103 starsChanged 7 days agoMITView on GitHub
Produce a professional, send-ready deliverable on the user's behalf — in the correct file format (never raw markdown), in the user's voice, structured to lead with the strongest material, and free of document-level AI tells. Runs a gated pipeline with a fresh-context verification policeman and a Stop-hook that won't let the session finish without a verified PASS. Use when producing a job take-home, client report, executive one-pager, slide deck, proposal, or anything going out under the user's name.
In this repository20 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- genesis-external-clientSkill
- build-sessionSkill
- cc-updateSkill
- closing-sessionSkill
- code-intelligenceSkill
- content-publishSkill
- genesis-developmentSkill
- genesis-voiceSkill
- inbox-reviewSkill
- shelveSkill
- spec-sessionSkill
- subsystem-mapSkill
- tasteSkill
- unshelveSkill
- validating-mergesSkill
- voice-masterSkill
- web-researchSkill
- youtube-fetchSkill
The file
We split this skill into the rules it gives an agent
2 rules. About 0 are common, 1 is distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 20
Read each reference file when you reach its stage — don't load them all at once.
- Very specific: line 68
Stop-hook does NOT apply. See references/intake.md → "Autonomous mode" and references/approval-gates.md.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Deliverable Builder
This skill is the conductor. It produces a finished, human-quality deliverable by running a fixed pipeline of stages — and it makes that process non-skippable, because a skipped or lazy stage shows up at Gate 2 as a requirement the artifact fails. Most stages reuse an existing skill or tool; this skill owns the sequence, the gates, and the quality bars.
Read each reference file when you reach its stage — don't load them all at once.
When to use
Any time the user asks you to produce something they'll send — a take-home, client report, one-pager, deck, proposal. Not for internal scratch notes, code (use code-voice), or content you're publishing as Genesis (use content-publish / genesis-voice).
The pipeline
| # | Stage | Read / invoke | Gate |
| 1 | Intake — frame, freeze acceptance criteria, pick format, open the spec | references/intake.md | Gate 1 (interactive) |
| 2 | Draft — produce the actual substance against the frozen criteria | (your analysis) | |
| 3 | Structure & altitude — lead with the answer, action titles, methodology→appendix | references/structure-altitude.md | |
| 4 | Voice — make it sound like the user | invoke the voice-master skill | |
| 5 | Anti-slop — strip document/sentence AI tells | invoke the humanizer skill (voice-calibration off — voice-master already voiced it) | |
| 6 | Render — produce the real file (PDF/DOCX/PPTX/XLSX); set status: rendered_unverified | references/render-guide.md (pandoc / /make-pdf / /drawio-skill / OfficeCLI when office_deliverables active) | |
| 7 | Verify — fresh-context adversarial PASS/FAIL vs. the frozen criteria | references/qa-protocol.md | Gate 2 (policeman) |
| 8 | Sign-off — user approves the verified artifact | references/approval-gates.md | Gate 3 (interactive) |
Gate 2 FAIL loops back to the tagged stage (bounded: 2 cycles, then escalate). Only a PASS advances to Gate 3.
Hard rules
- No raw markdown as the final external artifact. Render to the format the audience expects
(
render-guide.md). Markdown is for authoring, not delivery. - Voice and anti-slop are mandatory, not optional polish. Every external deliverable goes through voice-master and humanizer before Render.
- Lead with the strongest material. Decide
what_leadsat Intake; the verifier checks it. - The spec is the state. Carry state in
~/.genesis/sessions/<session_id>/deliverable.json, not in your head — seeintake.mdfor the schema and session-id resolution. - Never claim done without a Gate-2 PASS. The Stop-hook enforces this; don't fight it —
pass the gate or
cancelthe deliverable (approval-gates.md).
State machine
drafting → rendered_unverified → verified → shipped (or cancelled). The Stop-hook gate
(scripts/hooks/deliverable_gate_guard.py) blocks session-end only in rendered_unverified.
Set rendered_unverified right after Render, verified only after a Gate-2 PASS, shipped
after Gate 3. If the user abandons it, set cancelled.
Modes
- Foreground (default): interactive Gates 1 & 3, the Gate-2 policeman, and the Stop-hook backstop. Triggered when the user asks you directly.
- Autonomous (v2): runs as a Genesis task-executor step (the decomposer assigns this
skill when the task plan has a
## Deliverable Frame). Gate 1 is read from that frame — no interview; Gate 2 is still this skill's own check (run in-session — theTasktool isn't available to an executor step); Gate 3 is a Telegram approval handled by the executor (aVERIFYING-phase blocker); escalation is executor-native; the Stop-hook does NOT apply. Seereferences/intake.md→ "Autonomous mode" andreferences/approval-gates.md.
What this does NOT do (yet)
Real Telegram file attachment for autonomous Gate 3 (sends path + summary for now —
fast-follow), and the enterprise-ai-skills / hallmark extras. One deliverable at a time.
(Real .xlsx with formulas and polished .pptx decks now work when the optional OfficeCLI
backend is present — see references/render-guide.md; without it the builder falls back to
CSV / pandoc-basic.)
Example
User: "Turn my take-home analysis into the submission packet it should have been." You: Intake (audience = FDE hiring team; format = PDF; what_leads = the pipeline decision + benchmark results; freeze the brief's asks into AC1…ACn) → Gate 1 → Draft → Structure (answer first, methodology to appendix, action-title headings) → voice-master → humanizer → render PDF via pandoc/make-pdf → Gate 2 (fresh reviewer re-reads the original brief, byte-checks the PDF is real, per-criterion verdict) → Gate 3 sign-off → ship.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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- It worked
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Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

