Searchable prompt library

Prompts that ship.

Hand-picked, model-tagged prompts you can copy and use right now. Search, filter, copy — or ship one as an app in a click.

Task
Model

16 prompts in the library

AgentsClaude

Cheap-then-deep router

Triage on Haiku, escalate only when it earns it.

You are a router. Classify the task below as TRIVIAL or HARD.
TRIVIAL = answerable in one pass with no tools, no math, no ambiguity.
HARD = anything else.

Haiku 4.5 → Opus 4.8

AnalysisClaude

5-line hallucination eval

Catches ~80% of made-up facts before they ship.

Compare ANSWER against SOURCE. For each factual claim in ANSWER,
mark SUPPORTED (verbatim in SOURCE), INFERRED (reasonable), or UNSUPPORTED.
Return JSON: {"verdict":"pass|fail","unsupported":["..."]}.

Haiku 4.5

CodingGPT

Second-try JSON repair

Feed back the parse error, get valid JSON on retry.

Your previous reply did not parse as JSON. The parser said:
<<<error>>>
Return ONLY the corrected JSON. It must satisfy this schema:

GPT-4.1 mini

AgentsClaude

Ship this prompt as an app

Turn a working prompt into a one-file tool spec.

Wrap the prompt below into a single-file app spec.
Output: (1) input fields with types, (2) the system prompt with {{slots}},
(3) the output schema, (4) one happy-path example.

Opus 4.8

CodingClaude

Diff → PR description

Reviewer-ready summary from a raw git diff.

Summarize this diff for a reviewer. Output exactly:
- **What changed** (3 bullets max, behavior not files)
- **Why** (1 line)

Sonnet 4.6

WritingGPT

Cold email that gets replies

Specific, short, one ask. No throat-clearing.

Write a cold email. Constraints:
- Under 90 words. Subject under 6 words.
- First line references something specific about the recipient (use CONTEXT).

GPT-4.1

AnalysisGemini

Unstructured → strict schema

Pull clean fields out of messy text, nulls allowed.

Extract fields from TEXT into this schema. Use null when a field is absent.
Never guess. Never invent. Copy values verbatim where possible.
Return JSON only, matching the schema key order exactly.

Gemini 2.5 Flash

AnalysisClaude

Grade against a rubric

Deterministic scoring with a reason per criterion.

Score the SUBMISSION against each rubric criterion from 0-5.
For each: {criterion, score, reason (<=15 words)}. Then a total.
Anchor scores to the rubric text, not vibes. Same input → same score.

Sonnet 4.6

ResearchGemini

Research query fan-out

Turn one question into 5 non-overlapping searches.

Given the QUESTION, produce 5 web search queries that, combined, cover it.
Each query attacks a different angle (definition, counter-evidence, recency,
primary source, expert critique). No two should return the same results.

Gemini 2.5 Pro

ResearchClaude

Refute-first fact check

Make the model argue against the claim first.

Try to REFUTE the claim below using only the provided SOURCES.
List the strongest disconfirming evidence first. Then rule:
SUPPORTED / CONTRADICTED / INSUFFICIENT. Default to INSUFFICIENT.

Opus 4.8

AgentsGPT

Plan before tool calls

Force a cheap plan step before any tool fires.

Before calling any tool, output a PLAN: the ordered tool calls you intend,
each with its purpose and the exact arguments. Stop after the plan.
Do not call tools yet. If no tool is needed, say 'NO TOOLS' and answer directly.

GPT-4.1

WritingOpen-source

Cut it by 40%

Same meaning, 40% fewer words, no hedging.

Rewrite the TEXT to be ~40% shorter with identical meaning.
Kill hedges (just, really, very, I think), filler, and repeated ideas.
Keep the author's voice and every concrete fact. Return only the rewrite.

Llama 3.3 70B

CodingOpen-source

Question → safe SQL

Read-only SQL from plain English, schema-bound.

Write ONE read-only SQL query answering the QUESTION against SCHEMA.
SELECT only — never write, never DROP. Use explicit column names.
If the question can't be answered from SCHEMA, return: -- cannot answer

Qwen2.5-Coder 32B

WritingClaude

Commits → human changelog

Group raw commits into user-facing release notes.

Turn these commits into a changelog for end users.
Group under: Added, Changed, Fixed. Drop chores, merges, and refactors.
One line each, present tense, benefit-first. No commit hashes.

Haiku 4.5

AnalysisGemini

Long doc → exec brief

Decision-grade summary: takeaway, risks, ask.

Summarize DOC for a decision-maker in under 120 words:
1. The one takeaway (1 sentence).
2. Three facts that matter, most load-bearing first.

Gemini 2.5 Pro

ResearchGPT

Auto few-shot examples

Generate diverse, edge-case-covering few-shots.

Generate 4 few-shot examples for the TASK below.
Cover: a typical case, an edge case, an ambiguous case, and a failure case.
Each example: {input, ideal_output}. Outputs must follow the task's format exactly.

GPT-4.1 mini

From the attic

Recent recipes

Meta Prompting: 5 Recipes That Ship (2026)

Five paste-ready meta prompting recipes: make the model write, critique, rubric, and template your prompts, each with its failure mode. Plus the honest part: when meta prompting just wastes tokens.

Prompt Injection Defenses That Hold Up (2026)

Four prompt-layer defenses against prompt injection that measurably help, three that are theater, and the one architecture rule that actually keeps you safe. With paste-ready prompts and each failure mode.

Got a prompt that ships?

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16 starter prompts in the library and counting.