context-manager
Elite AI context engineering specialist mastering dynamic context management, vector databases, knowledge graphs, and intelligent memory systems.
17
3%
Does it follow best practices?
Impact
—
No eval scenarios have been run
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 as a marketing tagline rather than a functional skill description. It is packed with buzzwords ('elite', 'mastering', 'intelligent') but lacks any concrete actions, explicit trigger conditions, or clear scope boundaries. It would be nearly impossible for Claude to reliably select this skill over others based on this description alone.
Suggestions
Replace buzzwords with concrete actions, e.g., 'Builds and queries vector databases, constructs knowledge graphs, manages context windows for RAG pipelines.'
Add an explicit 'Use when...' clause with natural trigger terms, e.g., 'Use when the user asks about embedding storage, retrieval-augmented generation, context window optimization, or knowledge graph construction.'
Narrow the scope to a distinct niche — covering vector databases, knowledge graphs, AND memory systems is too broad and risks conflicting with more focused skills in any of those areas.
| 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 fails to clearly answer 'what does this do' in actionable terms and completely lacks any 'when should Claude use it' guidance. There is no 'Use when...' clause or equivalent trigger guidance. | 1 / 3 |
Trigger Term Quality | The terms used are technical jargon ('dynamic context management', 'vector databases', 'knowledge graphs') that users are unlikely to naturally say when requesting help. There are no natural user-facing trigger terms like 'search embeddings', 'store context', or 'build a RAG pipeline'. | 1 / 3 |
Distinctiveness Conflict Risk | The description is extremely broad, covering 'context management', 'vector databases', 'knowledge graphs', and 'memory systems' — each of which could be a separate skill. It would easily conflict with any skill related to databases, AI, memory, or knowledge management. | 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 masquerading as a skill file. It exhaustively lists capabilities, behavioral traits, and knowledge areas without providing any concrete, actionable guidance—no code examples, no specific tool commands, no validation steps, and no real workflows. The content would need a fundamental restructuring to be useful as an operational skill.
Suggestions
Replace the extensive capability lists with 2-3 concrete, executable workflows (e.g., a step-by-step RAG implementation with actual code for vector DB setup, chunking, and retrieval).
Add specific code examples for key tasks like vector database queries, knowledge graph construction, or context window optimization with real libraries and commands.
Remove the 'Behavioral Traits', 'Knowledge Base', and 'Example Interactions' sections entirely—they describe a persona rather than providing actionable instructions and waste significant token budget.
Move detailed reference material into bundle files (e.g., `resources/vector-db-patterns.md`, `resources/rag-implementation.md`) and keep SKILL.md as a concise overview with clear pointers.
| 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 rather than actionable instructions. Most of the 150+ lines are abstract capability listings that waste tokens without adding operational value. | 1 / 3 |
Actionability | No concrete code, commands, or executable examples 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 generic and lack any validation checkpoints, specific commands, or feedback loops. Steps like 'Analyze context requirements' and 'Design context architecture' provide no concrete guidance on how to actually perform these actions. | 1 / 3 |
Progressive Disclosure | There is one reference to `resources/implementation-playbook.md` for detailed examples, which is a good signal. However, no bundle files are provided to support this reference, and the massive amount of inline content (capability lists, behavioral traits, knowledge base) should have been split into separate reference files rather than bloating the main skill file. | 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
f5dc9e3
- Reviewed
Table of Contents
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