ia-refine-prompt

v3.0.4

Transforms vague prompts into precise, structured AI instructions. Use when asked to refine, improve, or sharpen a prompt, do prompt engineering, write a sys...

0· 285·0 current·0 all-time
byIlia Alshanetsky@iliaal

Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for iliaal/compound-eng-refine-prompt.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "ia-refine-prompt" (iliaal/compound-eng-refine-prompt) from ClawHub.
Skill page: https://clawhub.ai/iliaal/compound-eng-refine-prompt
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install compound-eng-refine-prompt

ClawHub CLI

Package manager switcher

npx clawhub@latest install compound-eng-refine-prompt
Security Scan
VirusTotalVirusTotal
Benign
View report →
OpenClawOpenClaw
Benign
high confidence
Purpose & Capability
Name and description match the SKILL.md and SPEC.md content. No unrelated env vars, binaries, or install steps are requested. All required behavior (refining prompts, validation, optional save) is coherent with the stated intent.
Instruction Scope
Runtime instructions are narrowly scoped to assessing, rewriting, validating, and optionally saving refined prompts. The skill explicitly forbids inventing missing facts and disallows refining harmful/illegal tasks. It only proposes writing to .ai/PROMPT.md with explicit user approval.
Install Mechanism
No install spec and no code files — instruction-only skill. This is the lowest-risk install posture and matches the skill's function.
Credentials
The skill requests no environment variables, credentials, or config paths. The only file path mentioned (.ai/PROMPT.md) is a user-visible save location and is written only after user confirmation.
Persistence & Privilege
always is false and the skill is user-invocable; autonomous invocation is allowed by platform defaults but not excessive here. The skill does not request persistent elevated privileges or modify other skills.
Assessment
This skill is coherent and low-risk: it only rewrites prompts and will not store anything without your confirmation. Before using, avoid pasting secrets or sensitive customer data into prompts (the skill's rules advise not to invent or store secrets). If you approve saving, the file will be appended to .ai/PROMPT.md in your environment — review that path and its contents if you have strict data-retention policies. Otherwise it is safe to install and use.

Like a lobster shell, security has layers — review code before you run it.

latestvk9767gsj96p1df5fsfem6kfdrs85mjr7
285downloads
0stars
11versions
Updated 17h ago
v3.0.4
MIT-0

Refining Prompts

Process

  1. Assess -- Identify what the prompt is missing:
ElementCheck
TaskIs the core action explicit and unambiguous?
ConstraintsAre length, format, tone, and scope defined?
Output formatDoes it specify the expected structure?
ContextDoes the model have enough background to act? Check: audience, input format, success criteria, scope boundaries, technical constraints
ExamplesWould a demonstration clarify the expected output?
Edge casesAre failure modes and boundary conditions addressed?
  1. Rewrite -- Transform into specification language: precise, imperative, no filler. Treat the prompt as a spec, not conversation.

  2. Validate -- Check the rewrite against the assessment table. Every gap identified in step 1 must be addressed.

Rules

  • Length: 0.75x–1.5x the original. Conciseness is a feature -- add only what's missing, cut what's vague.
  • Never invent -- only use information present in the original prompt or conversation context. If critical info is missing, ask instead of assuming.
  • Instruction hierarchy -- order sections by priority: task → constraints → examples → input data → output format. Place the most important instruction first.
  • Progressive complexity -- start with the simplest prompt that could work. Add few-shot examples, chain-of-thought, or role framing only when the task demands it, not by default.
  • Specific verbs -- replace vague actions ("analyze", "process", "handle") with measurable ones ("list the top 3", "classify as A/B/C", "return JSON with keys X, Y").
  • One output format -- specify exactly one format (JSON schema, markdown template, numbered list). Ambiguous format expectations cause inconsistent results.
  • No meta-commentary -- output only the refined prompt as markdown. No preamble ("Here's an improved version..."), no explanation of changes unless explicitly requested.

Persistence

After refining, offer to save the result to .ai/PROMPT.md -- do not write without user confirmation. If approved, append with a heading and date:

## [Prompt Name] -- YYYY-MM-DD

[refined prompt content]

Anti-Patterns

ProblemFix
Vague verbs ("look into", "deal with")Replace with concrete actions ("list", "compare", "extract")
Missing output specAdd explicit format section with example structure
Examples contradict instructionsAlign examples to match every stated rule
Over-engineered from the startStrip to simplest working version, then add complexity only where output quality requires it
Prompt exceeds context with examplesLimit to 2–3 diverse examples; use one simple, one edge case

Constraints

  • Stop refining if the original intent is unclear -- clarify first
  • Do not refine prompts for harmful or illegal tasks

Verify

  • Rewrite addresses every gap identified in the assessment
  • Length ratio within 0.75x-1.5x of original (unless structural change justified)
  • No invented constraints or assumptions not in the original

Comments

Loading comments...