prompt-engineering
Skill4 starsChanged 7 months agoMITView on GitHub
Effective prompting patterns for working with Claude, demanding quality, writing specs
85 other projects use a version of this, 1 of them edited.
Adopted by
Most recently taken up by
- ishandutta2007/Awesome-Claude-Skillstheir own version, first seen Nov 8, 2026
- kazemcodes/skill-treetheir own version, first seen Nov 8, 2026
- MMACABRE/SKILLStheir own version, first seen Nov 8, 2026
- Hoerire/Azurtheir own version, first seen Nov 8, 2026
- Bruno-Cunha-Souza/ValarMindSkillstheir own version, first seen Nov 8, 2026
- LuisSambrano/antigravity-configtheir own version, first seen Nov 8, 2026
Used with
Projects with it also use multi-agent-orchestration, llm-evaluation and 8 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
javalenciacaiSkillmulti-agent-orchestration
Design and coordinate multi-agent systems where specialized agents work together to solve complex problems. Covers agent communication, task delegation, workflow orchestration, and result aggregation. Use when building coordinated agent teams, complex workflows, or systems requiring specialized expertise across domains.
Also in 4 projects that use this
xfstudioSkillllm-evaluation
Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or establishing evaluation frameworks.
Also in 3 projects that use this
pproencaSkillrefactoring
Code refactoring best practices based on Martin Fowler's catalog and Clean Code principles. This skill should be used when refactoring existing code, improving code structure, reducing complexity, eliminating code smells, or reviewing code for maintainability. Triggers on tasks involving extract method, rename, decompose conditional, reduce coupling, or improve readability.
Also in 6 projects that use this
mjunaidcaSkilltool-design
Design tools that agents can use effectively. Use when creating new tools for agents, debugging tool-related failures, or optimizing existing tool sets.
Also in 3 projects that use this
LangChainSkillweb-research
Use this skill for requests related to web research; it provides a structured approach to conducting comprehensive web research
Also in 4 projects that use this
LuisSambranoSkillfirecrawl
Deep web scraping, screenshots, PDF parsing, and website crawling using Firecrawl API
Also in 3 projects that use this
Other versions85 projects use a version of this.
Word for word · 0
None found.
Edited · 1
- sefaertunc/anthropic-watch★ 1100% same
Wrote their own version · 84
- trycompai/comp★ 2.1ksame name
- niki914/zafiro★ 346same name
- CodeAlive-AI/ai-driven-development★ 169same name
- grandamenium/cortextos★ 106same name
- nahid-sparktales/agent-dispatcher★ 59same name
- geekatron/jerry★ 37same name
- Bbar0n234/learnflow-ai★ 35same name
- nimadorostkar/Claude-Skills-collection★ 33same name
- sabahattink/antigravity-fullstack-hq★ 30same name
- VoDaiLocz/kilo-kit-mcp★ 28same name
74 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository18 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- agent-routingSkill
- backend-conventionsSkill
- claude-md-maintenanceSkill
- coding-principlesSkill
- context-managementSkill
- coordinator-modeSkill
- frontend-design-systemSkill
- git-conventionsSkill
- memory-architectureSkill
- planning-with-filesSkill
- project-patternsSkill
- review-and-handoffSkill
- security-checklistSkill
- subagent-usageSkill
- testingSkill
- verificationSkill
The file
We split this skill into the rules it gives an agent
6 rules. 0 are common, 6 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 75 edited versions we read keep these.
6
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 24
When Claude produces a working but mediocre solution, push back:
- Distinctive: line 31
Don't accept the first output as final.
- Distinctive: line 44
Test case generation (give the categories, let Claude enumerate)
- Distinctive: line 52
Every feature described with concrete examples
- Distinctive: line 94
If Claude keeps making the same mistake, the problem is probably in your instructions, not in Claude.
- Distinctive: line 98
When Claude says "I'll do X" but you wanted Y, correct immediately.
“Common” is measured: kept by at least 6 in 10 of the 75 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Prompt Engineering
Challenge Claude to Do Better
Claude will give you a reasonable answer. You often want an excellent one. The difference is in how you ask.
Weak: "Write a function to parse dates." Strong: "Write a date parser that handles ISO 8601, RFC 2822, and common US/EU formats. It should return a consistent internal representation and throw specific error types for invalid input. Make it elegant — no regex spaghetti."
The strong version sets quality expectations, specifies edge cases, and demands craft. Claude responds to these signals.
Demand Elegance
When Claude produces a working but mediocre solution, push back:
- "This works but it's not elegant. Simplify it."
- "There's duplication between these three functions. Refactor."
- "This is too clever. Make it readable."
- "A junior engineer should understand this. Rewrite for clarity."
Don't accept the first output as final. Iterate.
When to Be Specific vs When to Delegate
Be specific about:
- Requirements (what the code MUST do)
- Constraints (performance, compatibility, patterns to follow)
- Verification criteria (how to know it works)
Delegate to Claude:
- Implementation approach (unless you have a strong preference)
- Variable naming and code organization details
- Which standard library functions to use
- Test case generation (give the categories, let Claude enumerate)
Writing Detailed Specs
A good spec eliminates ambiguity. The SPEC.md pattern works because it forces specificity before implementation begins.
Spec checklist:
- Every feature described with concrete examples
- Input/output pairs for non-obvious behavior
- Error cases listed explicitly
- "Out of scope" section to prevent feature creep
- Success criteria that can be mechanically verified
The IMPLEMENTATION-PROMPT as a Prompt
The implementation prompt IS your prompt to Claude for a work session. Write it like you're briefing a skilled contractor:
- Here's what exists (context)
- Here's what we need (goal)
- Here's how to do it (plan)
- Here's how to check your work (verification)
- Here's what NOT to do (constraints)
Prompting Anti-Patterns
- Vague asks: "Make the code better" — better HOW?
- Kitchen sink: asking for 10 things at once with no priority order
- Assuming context: referencing decisions made 500 messages ago without restating them
- Over-constraining: specifying the exact implementation when only the interface matters
- Under-specifying errors: "handle errors appropriately" — define what appropriate means
Working with Models at Different Levels
Opus: Use for judgment calls, architectural decisions, plan review. Give it the full picture and ask for analysis.
Sonnet: Use for implementation, testing, code review. Give it specific tasks with clear scope.
Haiku: Use for validation, formatting checks, simple queries. Give it narrow tasks with yes/no or pass/fail outcomes.
Match the task complexity to the model capability.
Gotchas
- Claude remembers everything in the conversation. You don't need to repeat instructions that are already in context. But after /compact, re-state critical constraints.
- If Claude keeps making the same mistake, the problem is probably in your instructions, not in Claude. Rephrase, add an example, or add a rule to CLAUDE.md.
- Long prompts aren't always better. A focused 3-line instruction often outperforms a rambling paragraph. Be concise about what matters.
- When Claude says "I'll do X" but you wanted Y, correct immediately. Don't let wrong assumptions propagate through a chain of actions.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

