Kjell Tore Guttormsen 79b6e29073 feat(humanizer): update audit/analysis command templates group A [skip-docs]

Wave 5 Step 13. Threads the humanizer vocabulary through five audit/
analysis command templates and adds a shape test that locks the
structure in place.

- commands/posture.md, tokens.md, feature-gap.md (findings-renderers):
  reference userImpactCategory/userActionLanguage/relevanceContext;
  remove hardcoded A/B/C/D/F-to-prose tables (humanizer owns the
  grade-context vocabulary now via the stderr scorecard headline).
- commands/manifest.md, whats-active.md (inventory CLIs): add --raw
  pass-through for CLI-surface consistency. --raw is a no-op in these
  CLIs, but the flag is threaded through so users get uniform behaviour.
- All five files: --raw flag parsed from $ARGUMENTS and passed verbatim
  to the underlying scanner CLI when present.

tests/commands/group-a-shape.test.mjs (new, +5 tests, 767 → 772):
  - structural: every file has a bash invocation block, Read tool
    reference, and --raw/$ARGUMENTS plumbing
  - findings-renderers only: at least one humanized field referenced;
    no hardcoded "[grade] grade is..." prose tables

2026-05-01 19:41:08 +02:00

3.3 KiB

Raw Blame History

name	description	argument-hint	allowed-tools	model
config-audit:manifest	Show ranked token-source manifest — every CLAUDE.md, plugin, skill, MCP server, and hook ordered DESC by estimated tokens	[path] [--json]	Read, Bash	sonnet

Config-Audit: Manifest

Produce a ranked, single-table view of every token source loaded for a given repo path. Where whats-active shows separate tables per category, manifest collapses everything into one ordered list — making it easy to see what's costing the most regardless of category.

UX Rules (MANDATORY — from `.claude/rules/ux-rules.md`)

Never show raw JSON or stderr output. Always use --output-file + 2>/dev/null.
Narrate before acting. Tell the user what you're about to do.
Read, don't dump. Read the JSON file and render a formatted table.
End with context-sensitive next steps.

Implementation

Step 1: Parse `$ARGUMENTS`

First non-flag argument is the path (default .). Recognized flags:

--json — emit raw JSON instead of the rendered table.
--raw — pass-through to the scanner; accepted for CLI surface consistency with the other config-audit commands. The manifest CLI is data-table only (no findings prose), so --raw is a no-op here, but the flag is still threaded through so users get uniform behaviour across --raw.

Step 2: Run the CLI silently

Tell the user: "Building token-source manifest for <path>..."

TMPFILE="/tmp/ca-manifest-$$.json"
RAW_FLAG=""
if echo "$ARGUMENTS" | grep -q -- "--raw"; then RAW_FLAG="--raw"; fi
node ${CLAUDE_PLUGIN_ROOT}/scanners/manifest.mjs <path> --output-file "$TMPFILE" $RAW_FLAG 2>/dev/null; echo $?

Exit code handling:

0 → continue
3 → tell user: "Couldn't read configuration. Check that the path exists and is a directory." Stop.

Step 3: If `--json` was requested, cat the file and stop

cat "$TMPFILE"

Do NOT render the table in JSON mode.

Step 4: Read JSON and render

Use the Read tool on $TMPFILE. Extract meta.repoPath, total, and sources[]. Render the top 20 sources (or fewer if the manifest is shorter):

**Token-source manifest for `<repoPath>`** — ~{total} tokens at startup

| Rank | Kind | Name | Source | Tokens |
|------|------|------|--------|--------|
| 1 | {kind} | `<name>` | {source} | ~{estimated_tokens} |
| ... | ... | ... | ... | ... |

_Estimates assume ~4 chars/token (Claude ballpark). Real token count varies ±15%._

If sources.length > 20, follow the table with: "Showing top 20 of {N} sources. Run with --json to see the full list."

Step 5: Suggest next steps

**Next steps:**
- `/config-audit tokens` — Opus-4.7 token-hotspot patterns (cache-breaking, redundant perms, deep imports, MCP budget)
- `/config-audit whats-active` — same data grouped by category, with disable suggestions
- `/config-audit feature-gap` — what *could* improve here, grouped by impact

Tone:

High total (>50k): empathetic — "That's a heavy startup cost; tokens bullet anything you'd otherwise spend on the actual conversation."
Moderate (10–50k): neutral — "Reasonable. Skim the top 5 to see if anything is unexpectedly large."
Low (<10k): encouraging — "Tight setup. The model has plenty of room for the actual work."

3.3 KiB Raw Blame History Unescape Escape