context-manager
Elite AI context engineering specialist mastering dynamic context management, vector databases, knowledge graphs, and intelligent memory systems.
37
3%
Does it follow best practices?
Impact
99%
1.00xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./skills/context-manager/SKILL.mdQuality
Discovery
0%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 reads like a resume headline rather than a functional skill description. It is packed with buzzwords ('elite', 'mastering', 'intelligent') and abstract concepts but fails to specify any concrete actions, natural trigger terms, or explicit usage conditions. It would be nearly impossible for Claude to reliably select this skill over others based on this description.
Suggestions
Replace abstract buzzwords with concrete actions the skill performs, e.g., 'Builds and queries vector databases, constructs knowledge graphs from documents, manages context windows for LLM applications.'
Add an explicit 'Use when...' clause with natural trigger terms, e.g., 'Use when the user asks about RAG pipelines, embedding storage, semantic search, or managing LLM context.'
Remove self-promotional language like 'Elite' and 'mastering' — descriptions should use third-person functional voice describing what the skill does, not how good it claims to be.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description uses vague, buzzword-heavy language like 'elite AI context engineering specialist' and 'intelligent memory systems' without listing any concrete actions Claude would perform. No specific operations like 'build', 'query', 'index', or 'retrieve' are mentioned. | 1 / 3 |
Completeness | The description vaguely gestures at a domain ('context management') but never explains what concrete tasks it performs (the 'what') and completely lacks any 'Use when...' clause or equivalent trigger guidance (the 'when'). | 1 / 3 |
Trigger Term Quality | The terms used are technical jargon ('context engineering', 'vector databases', 'knowledge graphs') that users are unlikely to naturally say when requesting help. There are no natural user-facing trigger terms like 'search my notes', 'remember this', or 'find related documents'. | 1 / 3 |
Distinctiveness Conflict Risk | The description is extremely broad and could overlap with any skill involving databases, memory, knowledge management, or AI systems. Terms like 'dynamic context management' and 'intelligent memory systems' are too generic to carve out a clear niche. | 1 / 3 |
Total | 4 / 12 Passed |
Implementation
7%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill is essentially a persona/role description rather than an actionable skill file. It consists almost entirely of abstract capability lists, behavioral traits, and knowledge areas that provide no concrete guidance for performing any specific task. There is no executable code, no specific tool commands, no concrete examples with inputs/outputs, and no meaningful workflow with validation steps.
Suggestions
Replace the extensive capability/trait/knowledge lists with concrete, executable examples for 2-3 core tasks (e.g., implementing a RAG pipeline, setting up a vector database, designing a context window strategy) with actual code snippets.
Add specific validation steps and feedback loops for key workflows, such as 'Test retrieval quality by running these queries and checking relevance scores above threshold X'.
Move the detailed capability taxonomy to a separate reference file and keep SKILL.md focused on actionable quick-start instructions with clear steps.
Remove the behavioral traits, knowledge base, and example interactions sections entirely—they describe what Claude should be rather than what Claude should do, and Claude already understands these concepts.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose with extensive lists of capabilities, behavioral traits, and knowledge areas that Claude already knows. The content reads like a persona description/resume rather than actionable instructions. Most of the 150+ lines are bullet-pointed descriptions of concepts Claude is already familiar with. | 1 / 3 |
Actionability | No concrete code, commands, specific examples, or executable guidance anywhere. The entire skill is abstract descriptions ('Dynamic context assembly and intelligent information retrieval') and vague instructions ('Apply relevant best practices and validate outcomes'). The 'Example Interactions' section lists prompts but provides no actual solutions or implementation patterns. | 1 / 3 |
Workflow Clarity | The 'Response Approach' section lists 10 high-level steps but they are entirely abstract ('Analyze context requirements', 'Design context architecture') with no concrete validation checkpoints, specific tools, or feedback loops. The main Instructions section has only four vague bullet points with no sequencing or verification details. | 1 / 3 |
Progressive Disclosure | There is one reference to an external file ('resources/implementation-playbook.md') which is good, but the main skill file is a monolithic wall of categorized bullet lists that should either be drastically condensed or split into separate reference files. The structure uses headers but the content under them is uniformly verbose lists. | 2 / 3 |
Total | 5 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 10 / 11 Passed | |
- Repository
- sickn33/antigravity-awesome-skills
- Commit
6a07b83
- Reviewed
Table of Contents
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