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context-window-management

Strategies for managing LLM context windows including summarization, trimming, routing, and avoiding context rot Use when: context window, token limit, context management, context engineering, long context.

49

Quality

62%

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tessl review fix ./cli-tool/components/skills/ai-research/context-window-management/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

33%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.

The body is a skeletal outline: a persona preamble (cut off mid-sentence), bare capability keywords, one-line pattern descriptions, and completely empty anti-pattern sections. While lean and well-sectioned, it provides almost no actionable guidance — no concrete strategies, thresholds, code, or decision workflow — so a Claude loading this skill would learn essentially nothing it doesn't already know.

Suggestions

Replace the persona preamble and dangling 'Your cor' fragment with concrete guidance: define the actual tier thresholds for the Tiered Context Strategy (e.g., token budget bands and what to do at each) and concrete techniques for summarization, trimming, and routing.

Flesh out the anti-pattern sections — 'Naive Truncation', 'Ignoring Token Costs', and 'One-Size-Fits-All' currently have no bodies; state what each looks like and what to do instead.

Turn the Patterns section into a sequenced decision workflow (assess context size -> choose strategy -> apply -> verify critical information survived), since workflow clarity is the lowest-scoring dimension.

DimensionReasoningScore

Conciseness

The body is short (~35 lines) with no padding that explains things Claude already knows, but the persona preamble ('You're a context engineering specialist who has optimized LLM applications handling millions of conversations... You understand that context is a finite resource...') is motivational framing that adds no actionable information and could be cut. This fits 'mostly efficient but includes some unnecessary explanation or could be tightened' rather than 4, since roughly a third of the body is this non-instructional persona text — plus a truncated dangling fragment ('Your cor').

3 / 5

Actionability

Guidance is limited to one-line high-level hints: 'Different strategies based on context size', 'Place important content at start and end', 'Summarize by importance, not just recency' — no code, commands, thresholds, or concrete methods, matching 'minimal concrete guidance; high-level hints but missing the specific steps'. It stays above 1 only because the pattern one-liners do state a directionally usable directive rather than being purely abstract, and the anti-pattern names ('Naive Truncation', 'Ignoring Token Costs') at least label real failure modes — though their bodies are empty.

2 / 5

Workflow Clarity

There is no sequence at all: the Patterns section presents three independent strategies, not steps, with no ordering, no decision guidance (when to summarize vs. trim vs. route), and no validation or checkpoints anywhere — matching 'steps missing or incoherent; no sequence; no validation'. It cannot score 2 because even a rough step sequence is absent; 'Tiered Context Strategy' gestures at context-size tiers but never defines the tiers or what to do at each.

1 / 5

Progressive Disclosure

The skill is under 50 lines with no bundle files (references/, scripts/, assets/ are absent), so under the simple-skill guideline only well-organized sections are required — and the headers (Capabilities, Patterns, Anti-Patterns, Related Skills) are clean and consistently used. It falls short of 5 because the 'Related Skills' list (`rag-implementation`, `conversation-memory`, etc.) points to skills with no paths or existence in the bundle, and the dangling 'Your cor' fragment shows the organization is not actually complete.

4 / 5

Total

10

/

20

Passed

Description

75%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 description that states what the skill does with four named strategies and provides an explicit, keyword-rich trigger list. Main weaknesses are the keyword-only 'when' clause, a missing sentence break between the capability list and the trigger list, and mild overlap risk with adjacent context-engineering skills.

DimensionReasoningScore

Specificity

The description lists several concrete actions — 'summarization, trimming, routing, and avoiding context rot' — naming the domain plus multiple specific capabilities, matching the 'several specific actions; minor gaps' anchor. It falls short of 5 because capabilities the skill body itself claims (prioritization, token counting) are absent, and the actions are named without any detail on how they operate.

4 / 5

Completeness

Both parts are present: a clear 'what' ('Strategies for managing LLM context windows including summarization, trimming, routing...') and an explicit 'when' ('Use when: context window, token limit...'). This matches the 'both present; when could be more explicit or specific' anchor rather than 5, because the trigger is a bare keyword list rather than concrete user-facing phrases, and a missing period between 'context rot' and 'Use when' blurs the boundary between the two parts.

4 / 5

Trigger Term Quality

'Use when: context window, token limit, context management, context engineering, long context' covers good natural terms a user would plausibly say, fitting the 'good keyword coverage; a few natural terms missing' anchor. It misses common variations like 'tokens running out', 'trim the conversation', or 'context overflow', keeping it below the comprehensive-with-synonyms anchor.

4 / 5

Distinctiveness Conflict Risk

The context-window-management niche is fairly distinct and its triggers ('token limit', 'context window') point clearly at this skill, fitting 'mostly distinct; minor overlap risk'. It doesn't reach 5 because 'context management' and 'context engineering' are broad terms that could also plausibly fire for adjacent skills like prompt caching, RAG, or conversation-memory skills.

4 / 5

Total

16

/

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

davila7/claude-code-templates

Path

cli-tool/components/skills/ai-research/context-window-management/SKILL.md

Reviewed

Table of Contents

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