ahepi/deepreason/assembly

Claude Code and agent skill by ahepi/deepreason

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How an LLM agent selects, installs, and glues the machine's modules (gate, driver, checkers, skills) for a NEW task or repository. Use when setting up any workflow from these tools, deciding which pieces a task needs, or wiring a new artifact type into gated production. Enforces minimal installation and the standard glue patterns.

Install

npx vskill@latest install ahepi/deepreason/assembly

SKILL.md

Assembly (gluing the machine's pieces)

<!-- PROMPT-CORE-BEGIN --> You are assembling a workflow from independent modules (see MODULES.md, provided as read context). Rules:

  1. MINIMAL INSTALL: list what the task actually requires before copying

anything. A module not named by the task's acceptance command or skill is not installed. Models (the driver, M2) come LAST and only if unattended generation is actually wanted -- most workflows are complete without them.

  1. Decide the three glue questions in order:

a. What is "done"? -> a deterministic COMMAND with exit codes. If no checker exists for the artifact type, the FIRST task is building one (single stdlib file + a FORMAT.md grammar, following battery_digest.py as the template) -- never a model judging doneness. b. Who must not collide? -> if more than one actor or session will write, install the gate (M1) and put every artifact in a cone. One actor, one session: the gate is optional; evidence still says commit early. c. Who generates? -> humans or a chat agent: give them the relevant M4 skill prompt-cores directly. Unattended: install the driver, write the stage in treadle.toml with the skill, the checker as acceptance, and any grammar files as context_files (a skill may never demand conformance to a file the model cannot read).

  1. STANDARD GLUE PATTERNS -- do not invent alternatives:
  • acceptance = checker invocation, exit code is the verdict;
  • grammars live in the repo (FORMAT.md files) and reach models as

READ-ONLY REFERENCE context, never inlined into skills;

  • proposals have no authority: generated artifacts count only after

the checker passes; a model's failure claim is evidence about the model, not the domain;

  • every new artifact type gets: a grammar, a checker, a skill, a

stage -- in that order.

  1. Report the assembly as a table (module -> why installed / why

skipped) before running anything. If the task fits no module and no checker can be defined, say so plainly: this machine only produces what it can deterministically accept. <!-- PROMPT-CORE-END -->

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