agentic-jujutsu
Quantum-resistant, self-learning version control for AI agents with ReasoningBank intelligence and multi-agent coordination
49
Does it follow best practices?
If you maintain this skill, you can automatically optimize it using the tessl CLI to improve its score:
npx tessl skill review --optimize ./path/to/skillEvaluation — 81%
↑ 1.26xAgent success when using this skill
Validation for skill structure
Discovery
7%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This description is heavily padded with marketing buzzwords and technical jargon while failing to communicate any concrete capabilities or usage triggers. It tells Claude nothing about what actions the skill performs or when to select it. The description prioritizes sounding impressive over being functional.
Suggestions
Replace buzzwords with concrete actions: specify what version control operations this skill performs (e.g., 'Track file changes, create branches, merge code, resolve conflicts').
Add an explicit 'Use when...' clause with natural trigger terms users would say (e.g., 'Use when the user mentions git, commits, branches, version history, or tracking changes').
Remove or clarify jargon like 'ReasoningBank intelligence' and 'quantum-resistant' - either explain what these mean in practical terms or remove them entirely.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description uses abstract buzzwords ('quantum-resistant', 'self-learning', 'ReasoningBank intelligence') without describing any concrete actions. No specific operations like 'commit', 'merge', 'branch', or 'track changes' are mentioned. | 1 / 3 |
Completeness | Missing both clear 'what' (no concrete actions described) and 'when' (no explicit trigger guidance or 'Use when...' clause). The description is entirely abstract with no actionable information. | 1 / 3 |
Trigger Term Quality | Contains technical jargon and marketing terms that users would never naturally say. Terms like 'quantum-resistant', 'ReasoningBank intelligence', and 'multi-agent coordination' are not natural user queries for version control tasks. | 1 / 3 |
Distinctiveness Conflict Risk | While the buzzwords are unique, 'version control' is a recognizable domain that provides some distinctiveness. However, the vague nature could still cause confusion with other version control or AI coordination skills. | 2 / 3 |
Total | 5 / 12 Passed |
Implementation
50%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill provides comprehensive, executable code examples but suffers from severe verbosity with marketing-style content, redundant examples, and explanations of basic concepts. The content would benefit greatly from aggressive trimming to focus on essential patterns and moving detailed API references to separate files.
Suggestions
Remove marketing language and statistics ('23x faster', '87% success rate') - focus on how to use the tool, not why it's good
Consolidate the 4+ similar trajectory examples into 1-2 canonical examples that demonstrate the pattern
Move the API Reference tables and Performance Characteristics to a separate REFERENCE.md file
Add explicit validation checkpoints in workflows (e.g., 'verify trajectory was recorded before proceeding')
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose at 500+ lines with extensive marketing language ('23x faster', 'quantum-resistant'), redundant examples showing the same concepts multiple times, and explanations of concepts Claude already knows (what version control is, how async/await works). | 1 / 3 |
Actionability | Provides fully executable JavaScript code examples throughout, with copy-paste ready snippets for all major operations including installation, basic usage, trajectory management, and error handling. | 3 / 3 |
Workflow Clarity | Multi-step processes are shown (start trajectory → do work → add → finalize) but lack explicit validation checkpoints. Error handling examples exist but don't show verification steps before proceeding with risky operations. | 2 / 3 |
Progressive Disclosure | References external documentation (VALIDATION_FIXES_v2.3.1.md, AGENTDB_GUIDE.md) but the main file is a monolithic wall of text with extensive inline content that should be split into separate reference files. The API reference tables could be in a separate file. | 2 / 3 |
Total | 8 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 9 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
skill_md_line_count | SKILL.md is long (646 lines); consider splitting into references/ and linking | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 9 / 11 Passed | |
- Reviewed
Table of Contents
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