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context-optimization

Context optimization extends the effective capacity of limited context windows through strategic compression, masking, caching, and partitioning. The goal is not to magically increase context windows but to make better use of available capacity.

Quality

59%

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tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills/skills/context-optimization/SKILL.md

The canonical home for this skill is context-optimization in administrakt0r/AI-Agents-Safe-Coding-Skills

SKILL.md
Quality
Evals
Security

Quality

Content

42%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-organized overview of four real optimization strategies with useful decision heuristics, but it is held back by verbatim repetition, background exposition, non-executable code examples, no ordered implementation workflow, and a dangling reference to a nonexistent file. Tightening the prose and either implementing or removing the pseudocode helpers would raise the two heaviest-weighted dimensions.

Suggestions

Delete duplicated content: the opening paragraph (verbatim copy of the description), the second occurrence of 'The art lies in selecting what to keep versus what to discard', and the 'Skill Metadata' footer.

Replace pseudocode snippets with executable implementations, or fold the undefined helpers (compact_context, store_observation) into a runnable script under scripts/ and reference it by path.

Fix the dangling reference: either point to a real file (e.g., references/optimization-techniques.md) with a markdown link, or remove the 'Internal reference' section; and merge 'When to Use' with the 'Optimization Decision Framework' into one ordered measure-diagnose-apply-verify workflow.

DimensionReasoningScore

Conciseness

There is noticeable padding: the opening paragraph repeats the frontmatter description verbatim; 'The art lies in selecting what to keep versus what to discard' appears twice (Core Concepts and Compaction); 'When to Use' overlaps the 'Optimization Decision Framework' triggers; sections explain background Claude already knows (what the KV-cache is, that 'context quality matters more than quantity'); and a 'Skill Metadata' footer adds no instruction. This matches 'noticeably verbose; several unnecessary explanations or padded sections' rather than the mostly-efficient level 3.

2 / 5

Actionability

Concrete guidance exists (masking tiers 'Never mask / Consider masking / Always mask', compression priorities, budget categories, numeric triggers like 'above 80%' and '50-70% token reduction'), but the three code examples call undefined helper functions (compact_context, store_observation, extract_key) — illustrative pseudocode rather than executable code — matching 'some concrete guidance but incomplete; pseudocode instead of executable code'. It is not 4 because no example can run or be adapted without inventing the missing implementations.

3 / 5

Workflow Clarity

A usable condition-to-technique mapping exists ('Tool outputs dominate: observation masking', 'Message history dominates: compaction with summarization') plus measurement triggers, but the skill never sequences these into an ordered procedure (measure, diagnose composition, apply technique, verify against the 50-70%/5% targets, iterate) — checkpoints are implicit and scattered across sections. This fits 'steps listed but validation gaps; sequence present but checkpoints missing or implicit', not level 4's clear sequenced workflow.

3 / 5

Progressive Disclosure

The body has good section structure, but it cites 'Internal reference: Optimization Techniques Reference - Detailed technical reference' with no filename or path, and no such file exists in the bundle (no references/ directory), so the reference is unverifiable and not clearly signaled. Detailed topic sections (masking tiers, cache patterns, summary-preservation tables) are inlined where a real reference file would be appropriate — matching 'references present but not clearly signaled; content that should be separate is inline' rather than level 4's mostly-clear reference structure.

3 / 5

Total

11

/

20

Passed

Description

58%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A solid, specific 'what' statement naming four optimization techniques in third person, but it is missing any 'when to use' trigger guidance, which both caps completeness and weakens trigger-term quality. Adding a 'Use when...' clause with natural user phrasings would lift the two lowest dimensions.

Suggestions

Append an explicit trigger clause, e.g.: 'Use when context limits constrain task complexity, token costs or latency are rising in long conversations, or when building long-running agent systems.'

Include natural user phrasings as trigger terms such as 'context limit', 'token limit', 'context too long', or 'compact the conversation' alongside the technical vocabulary.

State the actions as concrete verb-object operations (e.g., 'compacts conversation history near limits, elides stale tool outputs, reorders prompts to maximize KV-cache hits') rather than abstract strategy nouns.

DimensionReasoningScore

Specificity

The description lists several specific actions — 'strategic compression, masking, caching, and partitioning' — naming four concrete techniques, matching the 'several specific actions with minor gaps' anchor. It falls short of 5 because the actions are abstract strategy categories rather than concrete verb-object operations (e.g., 'compacts conversation history', 'reorders prompts for cache hits'), and it does not reach 3 since it names multiple techniques rather than only one or two.

4 / 5

Completeness

The 'what' is clearly stated ('extends the effective capacity of limited context windows through strategic compression, masking, caching, and partitioning') but the 'when' is entirely absent — there is no 'Use when...' clause or equivalent trigger guidance, which caps completeness at 3 per the judging guidelines. It is not 2 because the 'what' is clear and specific, and not 4 because no trigger guidance exists at all, explicit or weakly implied.

3 / 5

Trigger Term Quality

It includes relevant keywords like 'context optimization', 'context windows', 'compression', 'masking', 'caching', but misses the natural phrases users actually type when hitting this need: 'context limit', 'token limit', 'context too long', 'summarize the conversation'. This matches 'some relevant keywords but missing common variations or synonyms'; it is not 4 because everyday trigger phrasings are largely absent in favor of technical terminology.

3 / 5

Distinctiveness Conflict Risk

The phrase 'limited context windows' plus the four named techniques carve out a fairly distinct niche (context-window capacity engineering) with only minor overlap risk against closely related skills like context-fundamentals or memory-systems. It is not 5 because the topic boundary with adjacent context-engineering skills is soft, and not 3 because the named techniques are specific enough that a query about compaction or context caching would land here rather than on a generic skill.

4 / 5

Total

14

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository

administrakt0r/AI-Agents-Safe-Coding-Skills

Path

plugins/AI-Agents-Safe-Coding-Skills/skills/context-optimization/SKILL.md

Reviewed

Table of Contents

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