io.github.rishiatlan/claude-prompt-optimizer

MCPcommunity
v2.2.2io.github.rishiatlanUnknownUpdated 4mo agonpmGitHub

Scores, compiles & optimizes prompts for any LLM. Zero AI calls inside. Freemium.

The control plane for AI prompts. Score, enforce policy, lock config, and audit every prompt decision. Free tier included. Prompts run without any quality check. "Make the code better" gives Claude no constraints, no success criteria, and no target — leading to unpredictable results and wasted compute. No structure scoring, no ambiguity detection. Even experienced engineers skip success criteria,…

Automatically indexed from public sources. Not yet verified by the developer on Forge.Claim this listing →
4mo agoLast update
Package
Authorio.github.rishiatlan
LicenseUnknown
Version2.2.2
Sourcemcp-registry
Trust Status
B
60/100Good
Listed in Forge index+10/10
Publisher identity verified+0/25
Publisher: run `forge publish` from the package repo to claim ownership
Ed25519 publish signature+0/10
Included automatically when the publisher runs `forge publish`
Domain verification+0/5
Publisher: host /.well-known/forge.json on the package homepage with { "publisher": "<github-login>" }
CVE scan · clean+30/30
Static analysis · clean+20/20
npm provenance (Sigstore)+0/5
Publish from GitHub Actions with the --provenance flag
Paste into Claude Code, Cursor, or any AI assistant to fix all gaps
StatusCommunity-indexed
PublisherUnverified
SignatureUnsigned
Domain
Provenance
Dependencies60 resolved+ · none vulnerable
Tool surface20 tools · 1 privileged
Security scan✓ Cleanv5.0.2 · 20d ago
EvalsNone
IndexedJun 13, 2026

Verification confirms publisher identity (repo ownership), not code safety. The security scan covers known CVEs and suspicious install scripts — it cannot prove the absence of malicious code.

About

The control plane for AI prompts. Score, enforce policy, lock config, and audit every prompt decision. Free tier included. Prompts run without any quality check. "Make the code better" gives Claude no constraints, no success criteria, and no target — leading to unpredictable results and wasted compute. No structure scoring, no ambiguity detection. Even experienced engineers skip success criteria, constraints, and workflow steps. This linter flags structural gaps before you send. Cost is…

Keywords
mcp