reprompt

reprompt-cli (re:prompt) is a local-first CLI tool to scan and analyze prompts generated in AI coding tools. It provides a prompt dashboard, prompt scoring (research-calibrated), conversation distillation/compression, privacy checks for sensitive content exposure, and optional integrations such as a browser extension and an MCP server for certain tools. It claims analysis runs locally with no LLM calls/network requests for the scoring flows.

Evaluated Mar 30, 2026 (0d ago)
Homepage ↗ Repo ↗ DevTools ai prompt-engineering cli privacy local-first mcp analytics devtools python
⚙ Agent Friendliness
53
/ 100
Can an agent use this?
🔒 Security
54
/ 100
Is it safe for agents?
⚡ Reliability
39
/ 100
Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality
45
Documentation
70
Error Messages
0
Auth Simplicity
100
Rate Limits
0

🔒 Security

TLS Enforcement
50
Auth Strength
60
Scope Granularity
30
Dep. Hygiene
70
Secret Handling
60

Claims local analysis with no prompt text leaving the machine for core scoring. Includes privacy tooling and optional telemetry that sends only anonymous feature vectors (not prompt text) per README. However, no concrete details are provided here about telemetry transport/security, MCP auth, or how sensitive data is handled in logs/config files. Optional integrations (ollama/openai) could involve network calls and user-supplied API keys, so secret handling depends on implementation beyond the provided excerpts.

⚡ Reliability

Uptime/SLA
0
Version Stability
70
Breaking Changes
40
Error Recovery
45
AF Security Reliability

Best When

You want fast, local, repeatable prompt analytics across multiple coding assistants and you value privacy (local analysis; optional anonymous feature-vector telemetry).

Avoid When

You need a fully documented programmatic web API (OpenAPI/SDK) or strict, guaranteed no-telemetry guarantees without further audit.

Use Cases

  • Score and benchmark prompts for quality (structure/context/position/repetition/clarity)
  • Distill important turns from long debugging/feature-development conversations
  • Compress prompts to reduce token usage while preserving intent
  • Scan local machine/tool artifacts to discover prompts automatically (e.g., Claude Code/Cursor/Cline/Aider/Codex/Cursor)
  • Run a prompt quality linter in CI (e.g., score thresholds, PR comments)
  • Privacy review to understand what prompt/data was sent to which AI tools
  • Agent workflow analysis to detect error loops/tool patterns and identify inefficient sessions

Not For

  • A network-based hosted service for prompt optimization (it’s primarily local CLI tooling)
  • Regulated/guaranteed compliance workflows without independently verifying data handling and telemetry behavior
  • Using as an LLM inference provider or general chatbot
  • Environments requiring a documented REST/GraphQL API contract (none is evidenced in provided materials)

Interface

REST API
No
GraphQL
No
gRPC
No
MCP Server
Yes
SDK
No
Webhooks
No

Authentication

Methods: None for core local analysis (implied)
OAuth: No Scopes: No

No authentication scheme described for the CLI. MCP integration is mentioned as an optional extra, but auth configuration for MCP is not documented in the provided materials.

Pricing

Free tier: No
Requires CC: No

No pricing model described in provided materials; appears to be a local CLI package. Optional telemetry and optional integrations (e.g., Ollama/OpenAI) may incur downstream costs depending on user configuration.

Agent Metadata

Pagination
none
Idempotent
False
Retry Guidance
Not documented

Known Gotchas

  • No evidence in provided materials of an agent-oriented stable API/contract for MCP tool schemas, pagination, or retry semantics.
  • Most functionality appears local; agents expecting network-based behavior may need file-system/tool artifact access (e.g., scanning installed tools) that depends on local environment state.

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Scores are editorial opinions as of 2026-03-30.

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