Agent skill · data analytics · mvanhorn
printing-press-output-review
Internal sub-skill: agentic review of a printed CLI's sampled command output for plausibility issues that rule-based checks can't encode (substring-match relevance, format bugs, silent source drops, ranking failures). Invoked via the Skill tool by the main printing-press skill at Phase 4.85 and printing-press-polish SKILL.md during the diagnostic loop. Not for direct user invocation — its actionable wrappers are /printing-press and /printing-press-polish.
Why this skill is useful
Adds a specialized review process for CLI output that identifies plausibility issues beyond standard checks, enhancing the AI's diagnostic capabilities.
What it needs
Requires bash installed locally. About 6k tokens when loaded. Last updated 2026-08-06. 4,383 stars on the source repository.
What this skill does
printing-press-output-review (internal) Review the sampled outputs from a printed CLI for plausibility bugs that dogfood, verify, and the rule-based scorecard --live-check rules can't catch. Wave B policy: all findings surface as warnings, never errors. This skill is internal-only (user-invocable: false). It's invoked by parents — the main printing-press skill at its shipcheck Phase 4.85, and the printing-press-polish skill during its diagnostic loop. Running it standalone would produce floating findings text with no ship verdict, no fixes applied, no publish offer; the actionable wrappers are /printing-press and /printing-press-polish. The skill carries context: fork so the reviewer agent's diagnostic chatter stays isolated from the calling skill's context. Input The caller passes $CLIDIR as the argument: an absolute path to the printed CLI's working directory. What this catches Bugs that rule-based checks miss, typically surfaced by 5 minutes of hands-on testing but slipping past dogfood, verify, and scorecard --live-check rules: Substring-match results that coincidentally contain the query but don't match semantically (e.g., a query matches a substring of a larger unrelated term) Aggregation commands silently dropping sources when only some of the requested N come back Ranking or sort commands returning top-N results that aren't plausibly the best for the query (broken weights, extractor fallbacks) URLs in output pointing at category index pages, feed endpoints, or random-selector routes rather than canonical content permalinks Format bugs the rule-based layer doesn't catch (mojibake, inconsistent pluralization, truncated/wrapped cell content) Procedure Step 1: Gather sample data If the scorecard call fails or /tmp/output-review-livecheck.json is empty, return the SKIP result (Step 3) without dispatching the reviewer. Before dispatch, count entries in livecheck.features[] whose status is pass. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills mvanhorn/printing-press-output-review