Prompt Engineering Patterns
wshobson/agents
Reference for designing and tuning production LLM prompts: few-shot examples, chain-of-thought, structured outputs, templates and system prompts.
Diagnose and rewrite an underperforming LLM prompt so it produces reliable, well-structured output.
Install Prompt Optimizer
$ npx skills add mohitagw15856/pm-claude-skills --skill prompt-optimizer -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install mohitagw15856/pm-claude-skills prompt-optimizer --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/prompt-optimizer .claude/skills/prompt-optimizer && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "prompt-optimizer" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/prompt-optimizer into .claude/skills/prompt-optimizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "prompt-optimizer", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/prompt-optimizerType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add mohitagw15856/pm-claude-skills --skill prompt-optimizer -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install mohitagw15856/pm-claude-skills prompt-optimizer --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/prompt-optimizer .agents/skills/prompt-optimizer && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "prompt-optimizer" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/prompt-optimizer into .agents/skills/prompt-optimizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "prompt-optimizer", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mohitagw15856/pm-claude-skills --skill prompt-optimizer -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install mohitagw15856/pm-claude-skills prompt-optimizer --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/prompt-optimizer .cursor/skills/prompt-optimizer && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "prompt-optimizer" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/prompt-optimizer into .cursor/skills/prompt-optimizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "prompt-optimizer", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/mohitagw15856/pm-claude-skills.git --path skills/prompt-optimizer--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add mohitagw15856/pm-claude-skills --skill prompt-optimizer -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install mohitagw15856/pm-claude-skills prompt-optimizer --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/prompt-optimizer .gemini/skills/prompt-optimizer && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "prompt-optimizer" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/prompt-optimizer into .gemini/skills/prompt-optimizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "prompt-optimizer", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install mohitagw15856/pm-claude-skills prompt-optimizerInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add mohitagw15856/pm-claude-skills --skill prompt-optimizer -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/prompt-optimizer .github/skills/prompt-optimizer && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "prompt-optimizer" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/prompt-optimizer into .github/skills/prompt-optimizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "prompt-optimizer", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mohitagw15856/pm-claude-skills --skill prompt-optimizer -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install mohitagw15856/pm-claude-skills prompt-optimizer --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/prompt-optimizer .opencode/skills/prompt-optimizer && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "prompt-optimizer" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/prompt-optimizer into .opencode/skills/prompt-optimizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "prompt-optimizer", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
prompt-optimizer- GitHub stars
- 1.4k
- Token cost
- ~1.1k tokens
- SKILL.md length
- 570 words
- Files
- 1
- Skills in repo
- 1,348
- Repo updated
- First seen
- Licence
- MIT
At a glance
Diagnose and rewrite an underperforming LLM prompt so it produces reliable, well-structured output.
- Asked to improve a prompt
- SKILL.md covers Working from a brief, Required Inputs, Output Format and Quality Checks, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Fix a prompt that gives inconsistent
What it does
Prompt Optimizer is an agent skill from mohitagw15856/pm-claude-skills. Diagnose and rewrite an underperforming LLM prompt so it produces reliable, well-structured output. Use when asked to improve a prompt, fix a prompt that gives inconsistent or wrong results, reduce hallucination/refusals, or make output follow a format. Produces a rewritten prompt with a diagnosis of what was failing, the specific changes and why, and a small test set to verify the fix.
Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in AI & LLM Engineering, covering Prompt engineering and Structured output and tool calling. The repository describes itself as: 1255 professional Agent Skills for Claude, ChatGPT, Gemini, Cursor & Codex — PRDs, postmortems, leases, medical bills, layoffs, go-bags, new countries. Plain markdown, MIT, in… The licence is MIT.
When your agent uses it
- Asked to improve a prompt
- Fix a prompt that gives inconsistent
- Reduce hallucination/refusals
- Make output follow a format
Example prompts
- “/prompt-optimizer”
What it can do on your machine
Read from SKILL.md and the folder at commit 1cbf1f0. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Prompt Optimizer loads about 1.1k tokens when it runs. Until then it costs about 102 tokens; SKILL.md has 570 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from mohitagw15856/pm-claude-skills at commit 1cbf1f0, republished under its MIT licence (© mohitagw15856). 570 words, ~1,059 tokens.
Download SKILL.mdSave it as
.claude/skills/prompt-optimizer/SKILL.md (or your agent's skills folder).- name
- prompt-optimizer
- description
- Diagnose and rewrite an underperforming LLM prompt so it produces reliable, well-structured output. Use when asked to improve a prompt, fix a prompt that gives inconsistent or wrong results, reduce hallucination/refusals, or make output follow a format. Produces a rewritten prompt with a diagnosis of what was failing, the specific changes and why, and a small test set to verify the fix.
Prompt Optimizer Skill
A weak prompt fails in patterned ways — vague task, no output contract, buried instructions, no examples, or asking for judgement with nothing to ground it. This skill diagnoses which failure mode is in play and rewrites the prompt to fix it, then hands you a way to check the fix held — so "it's flaky" becomes a specific, testable change rather than another round of fiddling.
Working from a brief
You'll often get just the prompt and a vague "it's not working". Always deliver a full rewrite anyway — infer the intended task and output from the prompt's wording, state your assumptions, and rewrite. If the failing behaviour wasn't described, infer the most likely failure mode from the prompt's structure and say so. Never hand back only a critique with no rewritten prompt.
Required Inputs
Ask for these only if they aren't already provided (else infer and label):
- The current prompt — the exact text being used.
- What's going wrong — wrong answers, inconsistent format, refusals, too long/short, hallucinated facts.
- The desired output — what a perfect response looks like (a sample is ideal).
- Context — the model/runtime, whether it's one-shot or part of a chain, and any hard constraints (length, JSON, latency).
Output Format
Prompt Diagnosis & Rewrite
1. Diagnosis — the specific failure mode(s), each tied to the line that causes it:
| Symptom | Likely cause | Fix applied |
|---|---|---|
| Inconsistent format | no explicit output contract | added a schema + example |
| Hallucinated details | asked to answer without grounding | added "use only the provided context; say what's unknown" |
| Ignores an instruction | buried mid-paragraph | moved to a numbered rule near the top |
2. Rewritten prompt — the full new prompt in a fenced block, ready to paste. Apply the levers that fit: role + task in the first lines, an explicit output contract (structure/schema + a short example), grounding rules ("answer only from X; if unknown, say so"), constraints stated as rules not prose, and 1–3 few-shot examples when the task needs a demonstrated pattern.
3. What changed and why — a short bullet list mapping each edit to the symptom it addresses.
4. Test set — 3–5 concrete inputs (incl. an edge case and a "should refuse / say unknown" case) and the expected output for each, so the user can confirm the rewrite behaves before shipping.
Show full SKILL.md (197 more words)Show less
Quality Checks
- The rewrite has an explicit output contract (format/schema), not just a description of the task
- Each change is tied to a specific symptom — no cosmetic edits presented as fixes
- Grounding/uncertainty is handled (the model is allowed to say "I don't know")
- Few-shot examples are included only where a pattern must be demonstrated, not by default
- A test set with at least one edge case and one negative case is provided
- The prompt is ready to paste — no placeholders left unfilled
Anti-Patterns
- Do not return a critique without the rewritten prompt — the rewrite is the deliverable
- Do not pile on every technique at once — apply the levers that match the diagnosed failure, and say why
- Do not add examples that contradict the instructions — the model copies the example over the rule
- Do not make the prompt longer when the fix is to make instructions clearer and earlier
- Do not claim a fix works without a way to test it — ship the test set
Based On
Prompt-engineering practice — explicit output contracts, grounding/uncertainty handling, structured instructions, and example-driven demonstration.
Example Trigger Phrases
- "Improve a prompt."
- "Fix a prompt that gives inconsistent."
- "Reduce hallucination/refusals."
- "Make output follow a format."
© mohitagw15856, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in skills/prompt-optimizer of mohitagw15856/pm-claude-skills.
Open the folder on GitHubat commit 1cbf1f0
Compare with similar skills
Prompt Optimizer next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Prompt Optimizer this skillmohitagw15856/pm-claude-skills | 1.4k | — | ~1.1k | Automated safety check: Pass | MIT | |
| Prompt Engineering Patternswshobson/agents | 40k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Agent Prompt Quality Barmastra-ai/mastra | 29k | — | ~2k | Automated safety check: Pass | Custom licence | |
| Kayba Stage 2 Domain Contextkayba-ai/agentic-context-engine | 2.6k | — | ~1.9k | Automated safety check: Pass | Apache-2.0 | |
| Lintlanghermes-labs-ai/lintlang | 138 | — | ~719 | Automated safety check: Pass | Apache-2.0 | |
| Lintlang Audithermes-labs-ai/lintlang | 138 | — | ~1.9k | Automated safety check: Pass | Apache-2.0 |
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Questions about Prompt Optimizer
What does Prompt Optimizer do?
Diagnose and rewrite an underperforming LLM prompt so it produces reliable, well-structured output. Prompt Optimizer is an agent skill from mohitagw15856/pm-claude-skills. Diagnose and rewrite an underperforming LLM prompt so it produces reliable, well-structured output.
When should I use Prompt Optimizer?
Prompt Optimizer fits situations like: asked to improve a prompt; fix a prompt that gives inconsistent; reduce hallucination/refusals; make output follow a format.
How do I install Prompt Optimizer in Claude Code?
Run `npx skills add mohitagw15856/pm-claude-skills --skill prompt-optimizer -a claude-code`. Or copy the skill folder (skills/prompt-optimizer in mohitagw15856/pm-claude-skills) into .claude/skills/prompt-optimizer in your project. Claude Code loads it when a task matches its description.
How do I install Prompt Optimizer in Codex?
Run `npx skills add mohitagw15856/pm-claude-skills --skill prompt-optimizer -a codex`. Or copy the skill folder (skills/prompt-optimizer in mohitagw15856/pm-claude-skills) into .agents/skills/prompt-optimizer in your project. Codex loads it when a task matches its description.
Can I use Prompt Optimizer in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mohitagw15856/pm-claude-skills --skill prompt-optimizer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/prompt-optimizer, .gemini/skills/prompt-optimizer, .github/skills/prompt-optimizer and .opencode/skills/prompt-optimizer in your project.
What does Prompt Optimizer need to run?
SKILL.md names no scripts, command-line tools or credentials: Prompt Optimizer is instructions for the agent only.
Does Prompt Optimizer access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Prompt Optimizer safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Prompt Optimizer use?
Prompt Optimizer is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Prompt Optimizer use?
About 1.1k tokens (SKILL.md is roughly 4.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Prompt Optimizer?
Skills that share tags, products or a category with Prompt Optimizer: Prompt Engineering Patterns (wshobson/agents, 40k stars), Agent Prompt Quality Bar (mastra-ai/mastra, 29k stars), Kayba Stage 2 Domain Context (kayba-ai/agentic-context-engine, 2.6k stars) and Lintlang (hermes-labs-ai/lintlang, 138 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Prompt Optimizer?
mohitagw15856 (a GitHub user) maintains it in mohitagw15856/pm-claude-skills, which has 1,433 GitHub stars. The repository holds 1,348 skills in this directory. The repository was last updated on October 8, 2026.
Source: mohitagw15856/pm-claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.