By jklazinga
PM-native skills framework for AI coding agents. Discovery, spec, GTM, marketing, launch, and retro.
Map the competitive landscape - what alternatives exist, how they're positioned, where the gaps are, and what this means for product and GTM decisions.
Run a post-launch retro. Compare what was specced against what shipped, capture learnings, and update project context.
Explore a new idea, feature request, or problem through structured discovery before any spec is written.
Set up or refresh project context files. Run at the start of a new project or when context is missing or stale.
Run a structured critique of a draft spec to find ambiguities, missing edge cases, and assumption violations before engineering begins.
Triggers when the user wants to understand the competitive landscape - what alternatives exist, how they're positioned, where the gaps are, and what this means for the product. Also triggers if the user says 'competitive analysis', 'what are competitors doing', 'how do we compare', or 'who else does this'. Can run standalone or feed into discover, write-spec, or write-gtm.
Triggers after a feature has shipped. Compares what was specced against what was built, captures learnings, and feeds back into future discovery. Also triggers if the user says 'run a retro', 'close out this feature', or 'post-launch review'.
Triggers after all features inside an initiative have shipped and been closed. Evaluates the initiative thesis against what was observed. Distinct from close-feature - operates at the strategic level, not the feature level. Also triggers if the user says 'close the initiative', 'initiative retro', or 'did the initiative work'.
Triggers when the user describes a new idea, feature request, problem, or opportunity and no approved opportunity document exists for it yet. Explores it through structured questions before any spec or plan is written. Does NOT trigger if an opportunity document already exists for this feature with status: approved - in that case, ask the user if they want to proceed to write-spec.
Triggers when the bet is large, cross-cutting, or high-stakes - multiple teams, significant investment, or strategic importance. Runs before discovery to establish the strategic frame, stakeholder alignment, and stop condition. Does NOT replace discover - it precedes it.
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AI coding agents are good at building. They are not good at deciding what to build, writing specs that hold up, or knowing when a feature is actually done.
Fieldwork fixes that. It's a PM workflow for AI coding agents that covers the full feature lifecycle: discovery, spec, engineering handoff, GTM, launch, and retro. Skills trigger automatically based on where you are in the process, so you don't have to manage the workflow yourself.
Most PM tools for AI stop at strategy or stop at code. Fieldwork connects them. The discovery output feeds the spec. The spec feeds the implementation plan. The plan feeds your task tracker. The retro closes the loop against the prediction you made at discovery.
Every skill reads your actual codebase and product context. The outputs are grounded in what you know about your users, your OKRs, and your constraints, not generic templates.
Run these inside any Claude Code session:
/plugin marketplace add jklazinga/fieldwork-marketplace
/plugin install fieldwork@fieldwork-marketplace
Fieldwork is active in that project.
Tell Cursor Agent:
Fetch and follow the instructions at https://raw.githubusercontent.com/jklazinga/fieldwork/refs/heads/main/.cursor/INSTALL.md
Tell Codex:
Fetch and follow instructions from https://raw.githubusercontent.com/jklazinga/fieldwork/refs/heads/main/.codex/INSTALL.md
Tell OpenCode:
Fetch and follow instructions from https://raw.githubusercontent.com/jklazinga/fieldwork/refs/heads/main/.opencode/INSTALL.md
After install, describe your project or idea to the agent. If context files are missing, the onboard skill runs automatically. It will:
Once onboarding is done, describe a feature or opportunity. The agent takes it from there.
Not every idea needs a spec. Match the process to the bet.
Small or reversible bet. Key assumption testable by building. Use when the fastest way to learn is to make something, not document something.
spike → debrief → (if validated) discover or write-spec
Opportunity understood well enough to commit engineering time. Medium-sized bet.
discover → write-spec → review-spec → write-plan → scaffold-tasks → write-gtm → write-launch-brief → close-feature
Large, cross-cutting, or high-stakes. All gates required.
Same as Feature - no steps skipped.
onboard - Activates when context files are missing or stale. Reads your codebase, asks about your product and users, writes the three context files everything else depends on.
spike - Activates for small bets or when a key assumption is testable by building. Produces a test plan, not a spec. Time-boxed. Feeds back into discover if validated.
discover - Activates when you describe a new idea or opportunity. Asks clarifying questions, frames the problem, surfaces assumptions. Ends with a prediction: if this works, what will we observe? Saves an opportunity brief and assumptions log.
write-spec - Activates after opportunity approval. Writes a full product spec grounded in your context files. Structured for agent handoff - the spec is the execution brief.
review-spec - Activates after the spec is drafted. Reviews for gaps, contradictions, and missing edge cases. Asks: does this spec give us a real shot at the outcome we predicted in discovery? Flags issues before they become rework.
write-plan - Activates after spec approval. Produces a sequenced implementation plan grounded in the actual codebase.
scaffold-tasks - Activates after plan approval. Creates tracked tasks in GitHub Issues, Linear, or a local task file. MCP-aware - checks what's available before attempting any calls.
write-gtm - Activates after spec approval, in parallel with execution. Writes a go-to-market plan covering positioning, channels, and launch sequencing.
write-marketing - Activates after GTM approval. Writes a marketing brief for the feature: messaging, audience, and channel-specific copy direction.
write-launch-brief - Activates as launch approaches. Consolidates everything into a single launch brief for stakeholders and comms.
close-feature - Activates after the feature ships. Runs a structured retro that compares against the prediction made at discovery. Did we solve the customer problem?
npx claudepluginhub jklazinga/fieldwork --plugin fieldwork12 PM-specific agent skills, 6 workflow commands, 3 automation hooks for Product Managers
Agent-first PM toolkit with 9 specialist agents and 18 skills for solo developers and small teams
Theory-grounded product-thinking discipline for AI agents. 49 skills, 15 theory gates, six diamond scales (Purpose to Market). Discovery to delivery with evidence gates that block on insufficient evidence.
Spec-driven development for big features. When features get too big, plan mode gets too vague—leading to hallucinations during implementation. ShipSpec replaces vague plans with structured PRDs, technical designs, and ordered tasks that keep Claude grounded.
AI Coding Agent - PRD to tasks to implementation loop
AI skills framework: UNDERSTAND → ENVISION → DELIVER → REFLECT. Process enforcement, 14 workflows, 37 skills, 5 agent personas.