promptc 0.1.0

Measure worst-case context exposure in your Claude / Cursor setup.

promptc

Measure worst-case skill-context exposure in your Claude Code setup.

Status: v0.1.0 in development. Not yet published to PyPI; install from source.

What this is for

If you've been collecting Claude Code skills for a while, your .claude/ has probably grown faster than your attention to it. The same security rule lives in three different SKILL.md files. A skill description has gone stale and Claude is loading the whole 5,000-token body just to figure out it doesn't apply. There's no quick way to see this.

promptc analyze is a local-only audit: it walks your .claude/, catches duplicated paragraphs across skills, computes a worst-case "if Claude loads the body instead of just the description" multiplier, and gives you a Grade — A through F — so you can tell at a glance whether your setup is clean or has accumulated context debt.

All analysis runs locally. No data leaves your machine. No API keys required.

Install

git clone https://github.com/edenfunf/promptc
cd promptc
pip install -e .

(PyPI release lands with v0.1.1.)

Usage

promptc analyze .          # scans ./.claude/ if present, else .
promptc analyze .claude/
promptc analyze . --no-html --format json

Run promptc analyze --help for all flags (--threshold, --min-words, --exclude, --format, --open, …).

Sample output

Running on the included demo fixture:

$ promptc analyze examples/bloated-demo

+------------------------------------------------------------------------+
|                                                                        |
|                                D+                                      |
|                                                                        |
|             461 tokens of duplicate content across 5 files             |
|                     (32% of 1,446 scanned tokens)                      |
|                                                                        |
|             Plus 23.7x worst-case context exposure on top.             |
|                                                                        |
|                         Top offenders below.                           |
|                                                                        |
+------------------------------------------------------------------------+

File                          Role   Total  Body  Desc  Dup  Dup%
skills/code-review/SKILL.md   skill    286   270     8   38   14%
skills/python-style/SKILL.md  skill    290   272    10  129   47%
skills/security/SKILL.md      skill    314   291    16   99   34%
skills/sql-safety/SKILL.md    skill    284   266     9  134   50%
skills/testing/SKILL.md       skill    272   251    14   61   24%

Top duplicate groups:
  1. 244 tokens wasted (5 chunks, exact): all 5 SKILL.md files share
     an identical "Boundary discipline" paragraph
  2. 152 tokens wasted (5 chunks, near): an SQL-injection-prevention
     rule has been pasted across all 5 skills with minor wording tweaks
  ...

Full report: ./promptc-report.html

The HTML report adds a hero panel, a per-skill exposure breakdown, a side-by-side duplicate-rule view, and a methodology section that explains every formula.

What promptc does NOT do

• Cursor .cursor/rules/*.mdc: not yet scanned. If .cursor/ is detected next to .claude/, the CLI prints a warning so the gap is explicit. Tracked for v0.2.
• Token-cost dollars: report speaks tokens; conversion to a $ figure for a specific Claude pricing tier is a v0.2 nice-to-have.
• Auto-fix: promptc diagnoses, you decide. There is no promptc apply that rewrites your skills.
• Telemetry / phone-home: nothing. Local files in, local report out.

Glossary

• SKILL.md — the entrypoint file for a Claude Code skill. Lives at .claude/skills/<name>/SKILL.md. Only this file gets the skill role; supporting files (templates, references, examples) under the same directory are scanned as other.
• Duplicate-content ratio (a.k.a. bloat ratio) — share of total scanned tokens that promptc flagged as a near-duplicate of content elsewhere. Includes duplicates from supporting docs, not just SKILL.md bodies. Drives the Grade.
• Promised load — tokens for a SKILL.md's description frontmatter value. This is what Claude Code's docs say loads at session start.
• Worst-case load — tokens for a SKILL.md's body. The upper bound cost if the body ends up in context instead of just the description.
• Exposure multiplier — body_tokens / description_tokens. Both sides are content-only; frontmatter overhead is excluded from both.
• Insufficient state — promptc shows "Not enough to audit yet" when there are fewer than 3 SKILL.md files OR fewer than 1,000 aggregate body tokens across skills. Avoids misleading A+ grades on tiny setups.

The HTML report has a "How this is graded" section with the full formulae and threshold table.

Roadmap

• v0.1.x — --output PATH flag; cross-language SDK path detector (down-weights duplicate clusters whose paths only differ in /python/, /go/, etc); broader tokenizer calibration across CJK and pure-code corpora (initial English mixed prose/code sample shows cl100k_base underestimates Claude tokens by ~18%).
• v0.2 — .cursor/rules/*.mdc scanning; methodology calibration (replace heuristic A/B/C/D/F thresholds with a reference distribution derived from real .claude/ directories); --watch; share affordance for the HTML report.
• v0.3+ — semantic dedup (embedding-based, not just Jaccard); cross-binding language detector; $ cost conversion.

Development

pip install -e ".[dev]"
pytest
ruff check .

License

MIT