context-compression

tessl i github:muratcankoylan/Agent-Skills-for-Context-Engineering --skill context-compression

This skill should be used when the user asks to "compress context", "summarize conversation history", "implement compaction", "reduce token usage", or mentions context compression, structured summarization, tokens-per-task optimization, or long-running agent sessions exceeding context limits.

61%

Overall

Validation

Implementation

Activation

SKILL.md

Review

Evals

Validation

88%

Warnings & errors only

Criteria	Description	Result
skill_md_line_count	SKILL.md line count is 266 (<= 500)	Pass
frontmatter_valid	YAML frontmatter is valid	Pass
name_field	'name' field is valid: 'context-compression'	Pass
description_field	'description' field is valid (293 chars)	Pass
description_voice	'description' uses third person voice	Pass
description_trigger_hint	Description includes an explicit trigger hint	Pass
compatibility_field	'compatibility' field not present (optional)	Pass
allowed_tools_field	'allowed-tools' field not present (optional)	Pass
metadata_version	'metadata' field is not a dictionary	Warning
metadata_field	'metadata' field not present (optional)	Pass
license_field	'license' field is missing	Warning
frontmatter_unknown_keys	No unknown frontmatter keys found	Pass
body_present	SKILL.md body is present	Pass
body_examples	Examples detected (code fence or 'Example' wording)	Pass
body_output_format	Output/return/format terms detected	Pass
body_steps	Step-by-step structure detected (ordered list)	Pass
	Total	14 / 16 Passed

Implementation

63%

This skill provides solid conceptual coverage of context compression strategies with good workflow clarity and decision frameworks. However, it lacks executable code examples (only markdown templates) and is verbose for a skill document, explaining concepts at length rather than providing lean, actionable guidance. The content would benefit from being split into a concise overview with detailed references.

Suggestions

Add executable Python/pseudocode for implementing compression triggers and summary merging logic rather than just conceptual steps
Move detailed sections (evaluation dimensions, probe types, compression ratio tables) to separate reference files and link from a leaner main skill
Trim explanatory passages that describe 'why' at length - Claude understands trade-offs; focus on 'what to do'
Add a concrete code example showing how to detect context utilization and trigger compression programmatically

Dimension	Reasoning	Score
Conciseness	The skill is comprehensive but includes some explanatory content Claude likely knows (e.g., explaining what compression trades off, basic concepts). The tables and structured sections are efficient, but the overall length (~400 lines) could be tightened without losing actionable value.	2 / 3
Actionability	Provides conceptual guidance and structured examples but lacks executable code. The markdown summary templates are useful but the 'Implementing Anchored Iterative Summarization' section gives steps without concrete implementation code. No copy-paste ready compression functions or scripts.	2 / 3
Workflow Clarity	Clear multi-step workflows are present: the three-phase compression workflow, the anchored iterative summarization steps, and trigger strategies with explicit decision points. The 'When to Use Each Approach' section provides clear decision criteria.	3 / 3
Progressive Disclosure	Content is well-organized with clear sections, but the skill is monolithic with extensive inline content that could be split. References to other skills and external resources exist, but detailed topics like evaluation dimensions and probe types could be in separate reference files.	2 / 3
	Total	9 / 12 Passed

Activation

37%

This description is heavily imbalanced - it excels at trigger terms but completely lacks any explanation of what the skill actually does. It reads as a 'Use when...' clause without the preceding capability description. Without knowing the concrete actions (e.g., 'Creates structured summaries of conversation history, extracts key decisions and context'), Claude cannot make informed decisions about whether this skill is appropriate for a given task.

Suggestions

Add concrete capability statements before the trigger clause, e.g., 'Creates structured summaries of conversation history, preserves key decisions and context while reducing token count.'
Specify the outputs or results the skill produces, e.g., 'Generates compacted context documents that maintain essential information for long-running sessions.'
Restructure to follow the pattern: [What it does] + [Use when...] rather than only listing triggers.

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 specific capabilities like 'summarizes conversations', 'extracts key points', or 'reduces context by X%'.	1 / 3
Completeness	The description only answers 'when' (extensively) but completely fails to answer 'what does this do'. There is no explanation of the skill's actual capabilities or actions - it's entirely trigger-focused with no substance about functionality.	1 / 3
Trigger Term Quality	Excellent coverage of natural trigger terms users would say: 'compress context', 'summarize conversation history', 'reduce token usage', 'context compression', 'long-running agent sessions'. These are realistic phrases users would naturally use.	3 / 3
Distinctiveness Conflict Risk	The trigger terms are fairly specific to context/token management, but without knowing what the skill actually does, there's potential overlap with general summarization skills. Terms like 'summarize conversation history' could conflict with other summarization tools.	2 / 3
	Total	7 / 12 Passed

Reviewed

14 days ago

Table of Contents

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