context-optimization
This skill should be used when the user asks to "optimize context", "reduce token costs", "improve context efficiency", "implement KV-cache optimization", "partition context", or mentions context limits, observation masking, context budgeting, or extending effective context capacity.
69
61%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./skills/context-optimization/SKILL.mdQuality
Discovery
37%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 fundamentally incomplete - it functions as a trigger list rather than a skill description. While it excels at providing natural keywords users might say, it completely fails to explain what the skill actually does. A user or Claude cannot make an informed decision about whether this skill is appropriate without knowing its capabilities.
Suggestions
Add concrete actions at the beginning describing what the skill does (e.g., 'Analyzes and restructures prompts to reduce token usage, implements observation masking patterns, and partitions context for KV-cache efficiency.')
Restructure to lead with capabilities, then follow with 'Use when...' clause containing the existing trigger terms
Ensure the description uses third person voice with action verbs (e.g., 'Optimizes context windows', 'Reduces token costs', 'Implements caching strategies')
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description contains no concrete actions - it only lists trigger phrases without explaining what the skill actually does. There are no verbs describing capabilities like 'extract', 'analyze', or 'generate'. | 1 / 3 |
Completeness | The description only addresses 'when' (trigger conditions) but completely omits 'what' - there is no explanation of what actions or capabilities this skill provides. The 'what does this do' question is entirely unanswered. | 1 / 3 |
Trigger Term Quality | Excellent coverage of natural trigger terms users would say: 'optimize context', 'reduce token costs', 'improve context efficiency', 'KV-cache optimization', 'context limits', 'context budgeting'. These are realistic phrases users would naturally use. | 3 / 3 |
Distinctiveness Conflict Risk | The trigger terms are fairly specific to context/token optimization domain, but without knowing what the skill actually does, it's unclear if it would conflict with other optimization-related skills. The niche is somewhat defined but incomplete. | 2 / 3 |
Total | 7 / 12 Passed |
Implementation
85%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a strong, well-structured skill that provides actionable guidance for context optimization. The decision framework table, specific thresholds, and detailed Gotchas section are particularly valuable. The main weakness is some verbosity in explanatory passages that could be tightened without losing clarity.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is comprehensive but includes some unnecessary elaboration. Phrases like 'Effective optimization can double or triple effective context capacity without requiring larger models or longer windows — but only when applied with discipline' add flavor but not actionable value. The core concepts section could be tighter. | 2 / 3 |
Actionability | Provides concrete, executable code examples for compaction triggers, observation masking, and cache-friendly ordering. Includes specific thresholds (70% utilization trigger, 50-70% reduction targets), decision tables, and clear rules for what to mask vs preserve. | 3 / 3 |
Workflow Clarity | Clear priority ordering of techniques (KV-cache → masking → compaction → partitioning), explicit trigger conditions, and a decision framework table. The Gotchas section provides validation checkpoints and error recovery guidance (e.g., 'trigger compaction at 70-80%, not 90%+'). | 3 / 3 |
Progressive Disclosure | Well-structured with clear sections progressing from core concepts to detailed topics to practical guidance. References are one level deep and clearly signaled with 'Read when:' guidance. Integration section points to related skills without nesting. | 3 / 3 |
Total | 11 / 12 Passed |
Validation
100%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
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