# context-evaluator Evaluation **Resource**: context-evaluator — AI-powered CLAUDE.md / AGENTS.md quality analyzer **Source**: [github.com/PackmindHub/context-evaluator](https://github.com/PackmindHub/context-evaluator) **Web app**: [context-evaluator.ai](https://context-evaluator.ai) **Author**: Packmind engineering team **License**: MIT **Evaluated**: 2026-04-16 --- ## Score: 4/5 (High Value) **Decision**: Integrate — add to `guide/ecosystem/third-party-tools.md` (Configuration Quality section) and extract 2 patterns to `guide/core/skill-design-patterns.md`. --- ## What It Is context-evaluator analyzes CLAUDE.md and AGENTS.md files using 17 specialized AI evaluators (13 error + 4 suggestion categories). Available as: - Zero-install web app at context-evaluator.ai (paste a GitHub URL or upload a file) - Pre-compiled binary for macOS/Linux/Windows (no runtime dependencies) - Source install (Bun/TypeScript) Evaluation takes 1-3 minutes. Outputs a scored report with severity levels (Critical/High/Medium/Low) and specific fix recommendations. An automated remediation feature produces a `.patch` file for AI-generated improvements. --- ## Scoring Breakdown | Criterion | Score | Rationale | |-----------|-------|-----------| | Relevance to CC users | 5/5 | Directly evaluates the primary Claude Code config artifact (CLAUDE.md) | | Novelty vs. guide | 4/5 | LLM-based CLAUDE.md evaluation not covered; Caliber is deterministic only | | Technical quality | 4/5 | MIT, Bun/TypeScript, test coverage, pre-built binaries, 37KB CLAUDE.md | | Actionability | 5/5 | Zero-install web version + automated patch generation | | Engineering patterns | 4/5 | 2 new patterns not in guide: Runtime Prompt Logging, Adaptive Unified/Parallel Mode | **Overall: 4/5** --- ## Technical Patterns Identified (Source Read) ### Pattern 1: Runtime Prompt Logging (`runtime-prompt-logger.ts`) **Always-on blocking write to disk BEFORE the AI provider call.** Not a debug flag — every prompt is saved to `prompts/debug/` with an ISO-8601 timestamp filename, regardless of `--debug` flag state. The write is `await writeFile()` (blocking). If the provider call crashes or times out, the exact prompt is already on disk. Key design decisions: - Blocking write (not fire-and-forget): ensures the file exists before the AI call starts - Never throws: logging failures log a warning and return `null` but do not break evaluations - Separate from `--debug` (which saves to `{workingDir}/debug-output/`): this persists forever and is always active **Not in guide currently.** The guide covers `--debug` flag usage but does not name "write-before-invoke" as a design pattern for evaluator skills. ### Pattern 2: Adaptive Unified/Parallel Mode (`runner.ts:764-775`) **Token-threshold switching between single-agent and parallel-agent execution.** Before launching evaluators, the system estimates the combined token count of all input files. If below 100K tokens (`DEFAULT_MAX_UNIFIED_TOKENS`), all files are evaluated in a single unified agent call that can detect cross-file contradictions. If above, each file is evaluated by independent parallel agents. ```typescript export function canUseUnifiedMode( context: MultiFileContext, maxTokens: number = DEFAULT_MAX_UNIFIED_TOKENS, ): { viable: boolean; reason?: string } { if (context.totalTokenEstimate > maxTokens) { return { viable: false, reason: `Combined file content (~${context.totalTokenEstimate} tokens) exceeds limit (${maxTokens} tokens)`, }; } return { viable: true }; } ``` **Not explicitly named in guide.** The guide discusses parallel sub-agents and multi-file evaluation but does not document the "check token count, choose 1-agent vs N-agent" switching pattern with a concrete threshold. ### Pattern 3: Technical Inventory Injection (`context-identifier.ts`) CLOC + folder structure + `ls -la` analysis are collected first, then injected as structured context into all 17 evaluator prompts. Similar to Shared Ground Truth Injection (already documented in v3.39.0 `skill-design-patterns.md`). **No new documentation needed** — this is a variant of a pattern already covered. ### Pattern 4: Multi-layer deduplication Three-phase pipeline: rule-based clustering (location tolerance + text similarity) → AI semantic deduplication → impact curation. Interesting but specific to evaluation systems. Low value to general CC users, skip. --- ## Integration Decisions | Item | Decision | Rationale | |------|----------|-----------| | Tool mention in `third-party-tools.md` | Add | Directly useful, zero-install, higher value than Caliber for LLM-based review | | Runtime Prompt Logging in `skill-design-patterns.md` | Add | New pattern, 1 concrete implementation point | | Adaptive Unified/Parallel Mode in `skill-design-patterns.md` | Add | Concrete threshold-based decision not documented elsewhere | | Technical Inventory Injection | Skip | Variant of Shared Ground Truth (already in guide v3.39.0) | | Multi-layer deduplication | Skip | Too specific to evaluation pipelines | | Entry in `credits.md` | Add | Packmind repo, MIT license | --- ## Delta vs Caliber (in guide) | Feature | Caliber | context-evaluator | |---------|---------|-------------------| | No AI provider required | Yes | No | | Scoring rubric (0-100) | Yes | No | | Git drift detection | Yes | No | | LLM-based content review | No | Yes (17 evaluators) | | Cross-file analysis | No | Yes | | Automated remediation (patch) | No | Yes | | Zero-install (web) | No | Yes | context-evaluator and Caliber are complementary, not competitive. The guide should present them as options for different needs. --- ## Limitations - Requires AI provider (Claude Code, Cursor, OpenCode, GitHub Copilot, Codex) - Processing takes 1-3 minutes per run - No deterministic scoring rubric for CI gates - No git-based drift detection - Very new tool (launched 2026, Packmind experimental project) --- ## Files Modified - `docs/resource-evaluations/context-evaluator-evaluation.md` (this file) - `guide/ecosystem/third-party-tools.md` — new context-evaluator entry (Configuration Quality section) - `guide/core/skill-design-patterns.md` — 2 new patterns: Runtime Prompt Logging, Adaptive Unified/Parallel Mode - `guide/core/credits.md` — new entry for context-evaluator (MIT, Packmind) - `machine-readable/reference.yaml` — new entries - `CHANGELOG.md` — [Unreleased] entry