gz-content-compose

name	gz-content-compose
description	Validate and stage a candidate rendition from the corpus via gz content compose. Use when the agent has made compression decisions (drop/combine/rewrite of compressible corpus entries toward the declared setpoint) and wants the tool to validate invariant-floor compliance, compute byte evidence, write the candidate artifact, and emit a ledger event.
category	agent-operations
lifecycle_state	active
owner	gzkit-governance
last_reviewed	"2026-08-02T00:00:00.000Z"
metadata	{"skill-version":"1.0.1"}
model	sonnet
gz_command	gz content compose

gz-content-compose

Overview

Wield gz content compose to validate and stage a candidate rendition of a control surface toward a target consumer (vendor) at the declared compression setpoint. This is the compress stage of the ADR-0.0.37 CMS pipeline: corpus → compress → rendition → playback.

The tool is deterministic. NO LLM call, NO network I/O. The drop/combine/rewrite compression judgment is the agent's (this skill is the LLM surface). The tool validates, accounts bytes, and writes the candidate.

The tool NEVER writes a rendered surface. AGENTS.md, CLAUDE.md, and their mirrors are byte-unchanged after every compose run. Only the candidate artifact under .gzkit/renditions/ and the ledger change.

Workflow

1. Read the corpus for the target surface:
   • .gzkit/corpus/<surface>.jsonl — the append-only source of truth
   • Identify tier: invariant entries — these MUST appear verbatim in the candidate
   • Identify tier: compressible entries — these can be dropped, combined, or rewritten
2. Know the setpoint — resolve via gz validate --setpoint-coherence or read data/vendor-manifest.json content_type_temperatures.<ContentType>.<consumer>. The setpoint is lite, medium, or heavy.
3. Draft the candidate text — compress the compressible entries toward the setpoint:
   • lite: maximum compression; include only the highest-priority compressible entries
   • medium: balanced compression
   • heavy: minimal compression; include most compressible content
   • Invariant-tier entries MUST appear verbatim (0-Kelvin floor — no exceptions)
4. Write the candidate to a temp file (e.g. /tmp/candidate.md)
5. Run the compose tool to validate + stage:

gz content compose <surface> --consumer <vendor> --candidate /tmp/candidate.md

6. Confirm the output — check byte evidence and candidate path:

test -s .gzkit/renditions/<surface>/<consumer>.candidate.md
grep "composition_candidate_emitted" .gzkit/ledger.jsonl

7. The candidate flows to the advisor-QC loop (OBPI-24) and operator attestation (OBPI-22) before promotion to a committed rendition.

Output Contract

On success (exit 0):

• Candidate written to .gzkit/renditions/<surface>/<consumer>.candidate.md
• composition_candidate_emitted ledger event carrying surface, consumer, setpoint, and per-tier byte evidence
• Byte evidence printed to stdout

On failure (exit 1):

• No candidate written
• Error to stderr naming the cause (absent corpus / undeclared setpoint / invariant violation)

Do Not

• Call any Anthropic/LLM API in tool code — the tool is deterministic; this skill IS the LLM surface
• Auto-promote the candidate to a committed rendition — that is OBPI-22 scope
• Rewrite or drop tier: invariant entries in the candidate text
• Claim compose is complete without running gz content compose and confirming exit 0
• Edit AGENTS.md, CLAUDE.md, or any mirror during this skill — rendered surfaces are never touched