AI agent archive

Agent Archive

Find, use, and organize AI agents for every workflow.

A curated archive of AI agents, prompts, and workflow recipes for real work across planning, design, development, marketing, sales, and operations.

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Why agents make work easier

Start from the job to be done, then use the agent as a reusable structure for inputs, outputs, and review.

Start faster

Use input templates and expected output shapes instead of starting from a blank prompt.

Stabilize quality

Each agent gives review criteria, limits, and examples so results are easier to judge.

Improve handoffs

Requests, execution notes, and next steps become easier for teammates to reuse.

Overview

Agent Archive is not just a prompt list. Each entry is framed as a reusable work recipe with inputs, expected outputs, practical limits, and related agents.

Context first

Agents are organized around actual jobs to be done, not abstract prompt tricks.

Copy-ready prompts

Agents are organized around actual jobs to be done, not abstract prompt tricks.

Workflow packs

Agents are organized around actual jobs to be done, not abstract prompt tricks.

What changes when agents are used well

These example scenarios show the practical shift from scattered requests to reusable outputs, review criteria, and cleaner handoffs.

Engineering teams4 AgentsWorkflow-linkedLess reworkCleaner handoffEarlier QA

From loose feature idea to merge-ready handoff

A feature request reaches the developer as a vague paragraph, so implementation starts before scope, tests, and review criteria are aligned.

View workflow

Plain benefit

Turn an unclear request into a shared implementation brief before anyone starts editing code.

Best place to start

Start here when a feature idea is ready for development but the scope, files, and review criteria are still loose.

Before

Feature idea is scattered across chat, a ticket, and a short product note
Codex receives a broad request with missing files, constraints, and non-goals
QA and PR review happen late, after assumptions have already shaped the code

Agent flow

1
Feature Requirements Analyst
Transforms feature ideas into implementation-ready requirements.
2
Codex Task Brief
Creates precise implementation instructions for coding agents.
3
QA Checklist Agent
Builds practical QA checklists for releases and handoffs.
4
PR Review Agent
Reviews pull requests for correctness, regression risk, and missing tests.

Outputs created

Implementation-ready requirements · Codex task brief · Release QA checklist · Prioritized PR findings

After

The developer starts from acceptance criteria and explicit non-goals
Codex receives files, constraints, test plan, and expected behavior before editing
Review focuses on regression risk instead of rediscovering scope

Example impact

Fewer rewrite loops before implementation

Review quality

Findings tied to acceptance criteria

Team clarity

One shared brief for PM, developer, and reviewer

Product teams3 AgentsEvidence firstFaster prioritizationBetter tradeoffs

From raw customer feedback to roadmap decision

Customer feedback is plentiful, but themes, severity, and roadmap tradeoffs are not visible enough to make a confident decision.

Plain benefit

Group raw feedback into evidence-backed priorities before roadmap decisions are made.

Best place to start

Start here when feedback volume is high but the team is arguing from individual anecdotes.

Before

Support notes and sales comments are reviewed one by one
Roadmap discussion favors loud anecdotes over grouped evidence
The team leaves with priorities but weak rationale

Agent flow

1
Customer Feedback Clusterer
Clusters raw feedback into themes, severity, and next actions.
2
Feature Requirements Analyst
Transforms feature ideas into implementation-ready requirements.
3
Product Roadmap Prioritizer
Ranks roadmap items by impact, confidence, effort, and timing.

Outputs created

Feedback theme map · Feature requirement candidates · Prioritized roadmap with assumptions

After

Repeated problems are grouped by theme, severity, and evidence
Candidate features have clearer acceptance criteria and unresolved questions
Roadmap tradeoffs are visible before leadership chooses sequence

Example impact

Roadmap meeting starts from evidence clusters

Decision quality

Priority includes confidence and effort assumptions

Handoff value

Chosen items are closer to implementation briefs

Operations and founder-led teams4 AgentsWorkflow-linkedLess repetitionReusable SOPsFaster onboarding

From repeated explanations to reusable operating system

Recurring work is explained verbally every time, so quality depends on who happens to remember the process.

View workflow

Plain benefit

Convert recurring explanations into durable operating documents that teammates can reuse.

Best place to start

Start here when the same process is explained repeatedly or quality depends on one person's memory.

Before

Meeting notes, policy decisions, and process steps live in separate places
New teammates need repeated explanations before they can execute
Exceptions are handled from memory instead of a shared checklist

Agent flow

1
Meeting Summary Agent
Turns meeting transcripts into decisions, actions, and open questions.
2
Operations SOP Agent
Writes standard operating procedures for recurring work.
3
Policy Doc Writer
Drafts clear internal or product policy documents.
4
README Generator
Creates a concise README for a software project.

Outputs created

Decision and action summary · Standard operating procedure · Policy draft · Project README

After

Meetings turn into decisions, owners, and open questions
Recurring work has a trigger, owner, steps, exceptions, and quality checks
New teammates can follow a document instead of asking for the whole context again

Example impact

Less repeated explanation for recurring work

Process quality

Exceptions and checks are visible

Onboarding value

Documentation becomes the first handoff