Score
8.5
/ 10
Installs
47K
Repo Stars
97.9K
Last Updated
0d ago
Quality Ratio
91%
Description
Verified
Language
Go
First Published
Apr 2026
Summary
The Compress agent skill guides the AI to produce significantly shorter, more direct, and token-efficient responses. This is particularly beneficial for developers who need quick code snippets, specific configuration advice, or succinct explanations without verbose AI output. It is a moderately adopted skill within the registry. While specific implementation details from the SKILL.md are not provided, this agent skill likely achieves its conciseness by instructing the AI to prioritize brevity, avoid conversational filler, and focus strictly on delivering the requested information. It aims to streamline interactions, ensuring that responses are to-the-point and optimized for efficiency rather than extensive elaboration. Developers should be aware that extreme conciseness might occasionally omit context or deeper explanations that could be crucial for complex topics.
Skill Definition
Simplify skills, prompts, and instructions to the smallest text that still changes agent behavior.
Keep load-bearing words. Cut noise. Use dense command language.
Process
- Choose the target from
$ARGUMENTS, a pasted instruction, or the named file. - Extract the behavior contract: actions, inputs, outputs, tools, files, checks, constraints, defaults, edge cases, and stop conditions.
- For each sentence or bullet, run the output-change test: if removed, would the agent's output or process likely change?
- Delete it when the answer is no.
- Rewrite it when it points at a real requirement but uses vague language.
- Prefer load-bearing verbs: build, update, remove, keep, inspect, verify, return, skip, ask, stop, fail, retry, cite, preserve.
- Prefer specific nouns: file path, schema, command, tool, source, output format, test, threshold, owner, state, error, example.
- Preserve behavior. Do not weaken rules to make the text shorter.
- Cut:
- baseline agent virtues, such as "be thorough", "write clean code", "use good judgment", "make it easy to read", or "write a good commit message"
- quality adjectives without criteria, such as "robust", "polished", "detailed", "comprehensive", or "production-ready"
- motivational language
- throat-clearing, rationale, and backstory that do not alter the task
- restated rules
- overlapping instructions
- padding phrases
- obvious preamble
- hedging that does not change behavior
- examples that restate a rule without adding format or edge-case value
- Keep:
- commands and constraints
- concrete success checks
- concrete examples that show a required format or edge case
- file paths, exact names, identifiers, commands, and schemas
- instructions that came from previous failures
- defaults that resolve real ambiguity
- If asked to update a file, replace it with the simplified version. Otherwise return only the simplified instruction.
Rewrite
Rewrite weak phrases into commands only when the context supports a concrete behavior. Otherwise delete them.
- "Be thorough" becomes "Inspect open review threads, failing checks, and linked issues before reporting ready" only when those sources are in scope.
- "Make the commit message very detailed" becomes "Use a conventional commit subject and include a body with motivation, tests, and risk" only when that exact commit format matters.
- "Make the implementation easy to read" becomes "Keep parsing, validation, and rendering in separate functions" only when that boundary is relevant to the change.
- "Create a polished final answer" becomes "Report changed files and checks run" only when final-report evidence matters.
Output Shape
Use the simplest structure that preserves behavior:
- imperative bullets for rules
- numbered steps for required order
- short prose for one connected idea
- examples only for exact format or edge cases
Rules
- Return the simplified version only unless the user asks for commentary.
- Merge overlapping sections.
- State a general rule and its exception together.
- Do not drop a rule to hit a word count.
- Do not keep motivational or quality language unless it creates a concrete test, priority, or constraint.
- Replace vague quality language with a behavior-changing rule only when the original intent clearly requires it.
- If simplification changes likely agent behavior, restore the load-bearing instruction.