prd
Skill5 starsChanged 26 days agoMITView on GitHub
Interview the operator and write the strategic layer of a product —vision, problem, users, scope, competitors, opportunities, open questions, glossary— into the `context/` of its node in the brain, never into the body repo. Manually triggered, last link of the discovery pipeline and the gate before specs.
125 other projects use a version of this.
Adopted by
Most recently taken up by
- Adelie-Squad/solosquadtheir own version, first seen Nov 8, 2026
- shaqmughal/seekstonetheir own version, first seen Nov 8, 2026
- lhbsaa/apex-unifiedtheir own version, first seen Nov 8, 2026
- Jasenpan1987/multi-codetheir own version, first seen Nov 8, 2026
- joeldevz/skynex-pitheir own version, first seen Nov 8, 2026
- insight68/Skillstheir own version, first seen Nov 8, 2026
Used with
Projects with it also use context-optimize, usecase and 10 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.
ibahgatSkillcontext-optimize
Improve context efficiency and cache stability for long or complex sessions.
Also in 3 projects that use this
gabriellstSkillusecase
Create an application use case. Use when implementing business operations like CreateOrder, ProcessPayment, CancelBooking. Use this skill for any command/mutation that orchestrates domain logic, whether simple CRUD or complex multi-step transactions with sagas. Dispatch hub — routes to typescript/go variants by file extension.
Also in 3 projects that use this
jidechaoSkillmodern-go
Modernize Go code by applying version-appropriate idioms and APIs (gofix-style transformations). Scans go.mod for the Go version, then transforms Go source files to use modern patterns—from Go 1.0 through 1.26+. Use when the user says "现代化","现代Go语言", "地道的", "idiomatic", "modernize", "modern-go", "update Go code", "gofix", or wants to upgrade Go idioms.
Also in 3 projects that use this
ulises-jeremiasSkilltrd
WHAT — Draft and review a Technical Requirements Document (TRD) using the template, typically
Also in 3 projects that use this
jidechaoSkillloop-it
Automated issue loop with checkpoint/resume: fetch open GitHub issues → dependency-aware topological sort → implement each issue end-to-end → review with /review-it → document with /note-it → ship with /ship-it → repeat. Persists state to .loop-state.json for crash recovery. Triggers on: loop-it, loop issues, auto implement, 批量实现, 循环实现, 实现所有issue, 恢复循环, resume loop.
Also in 3 projects that use this
snarktankSkillralph
Convert PRDs to prd.json format for the Ralph autonomous agent system. Use when you have an existing PRD and need to convert it to Ralph's JSON format. Triggers on: convert this prd, turn this into ralph format, create prd.json from this, ralph json.
Also in 16 projects that use this
- +2 more from jidechao
Other versions125 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 125
- github/awesome-copilot★ 41ksame name
- snarktank/ralph★ 22ksame name
- SethGammon/Citadel★ 927same name
- smallnest/autoresearch★ 571same name
- snarktank/compound-product★ 542same name
- CatCatUncle/openworkbuddy★ 398same name
- smallnest/goal-workflow★ 283same name
- OffchainLabs/arbitrum-docs★ 252same name
- julianromli/ai-skills★ 215same name
- golbin/agent-skills★ 214same name
115 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 repository12 other files it gives its agents.
- cpoSkill
- ctoSkill
- grillSkill
- ideation-engineSkill
- insight-engineSkill
- market-researchSkill
- product-builder-resolverSkill
- product-metricsSkill
- product-strategySkill
- synthetic-usersSkill
- ux-researchSkill
- visual-designerSkill
The file
We split this skill into the rules it gives an agent
8 rules. 0 are common, 5 are distinctive, and 3 are very specific to this project.
0
Common
Most of the 102 edited versions we read keep these.
5
Distinctive
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 36
No file in this list is written into the body repo.
- Distinctive: line 53
Before the first question:
- Very specific: line 57
Read in full the files that context/ already has.
- Very specific: line 59
Read the context of the owning organization and, if it exists, the dated research that applies — it lives in the research/ of the node, …
- Distinctive: line 90
Before talking about what to build, the premise is challenged: is this the right problem?
- Distinctive: line 102
Before fixing the solution, 2 or 3 paths are presented, each with its effort, risk and what it reuses of what already exists:
- Distinctive: line 120
Before touching any file, the operator is shown exactly what is going to be written —the content, not a summary— and their go-ahead is …
- Very specific: line 135
The minimums gate: if glossary.md, scope.md or the architecture of the body are left empty, no specs come out of there yet.
“Common” is measured: kept by at least 6 in 10 of the 102 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
prd — the strategic layer of a product
It interviews the operator and produces the strategic definition of a product: vision, problem, users, scope, competitors, opportunities, open questions and glossary. It is the entry door to the method — out of this layer come the specs.
It always writes into the context/ of the loaded product node of the brain, never into the body
repo. The repo declared in repo: of the node's head is the body: specs, technical decisions,
as-built. The strategic layer lives in the head, not in the body.
The interview applies pressure with the method of .agents/skills/grill/SKILL.md#method: it is cited by that
heading, never copied. Any change to the method happens there, once.
The files it produces
They go into context/ of the loaded product node. If the node has no context/ yet, it is born
with README.md first and the rest as the interview gets completed.
| File | What it answers |
README.md | Index: what the product is, in what order each file was filled, its state |
vision.md | The finished system, where it gets to |
problem.md | What problem it solves, for whom, why now, how you know whether it worked |
users.md | Who it sells to, what they use instead today |
scope.md | What it does NOT do, who it does NOT sell to, hard constraints, what goes into the first version |
competitors.md | What it competes against and how it differs |
opportunities.md | What might be worth it and has not been decided |
open-questions.md | What is left to decide — live, it empties out as things close; the questions sit inside its [!QUESTION] callout |
glossary.md | The terms of the domain |
No file in this list is written into the body repo. If completing a section forced touching the body repo or a resolver, the tool does not do it: it says so and stops — that is a stopping condition of the spec that brought it, not a decision of this session.
Without a product node, these eight generic filenames do not land loose in whatever folder the
session started in, where they could overwrite files the user already had: they go into a
product-context/ folder of the current folder instead — product-context/vision.md,
product-context/problem.md, product-context/users.md, product-context/scope.md,
product-context/competitors.md, product-context/opportunities.md,
product-context/open-questions.md, product-context/glossary.md. With a product node loaded, the
destination stays context/ exactly as above, unchanged.
The KPI tree does not go here: it belongs to another tool's metric brief; this skill references it if it already exists, it does not produce it.
Phase 1 — Read what the brain already knows before asking
Before the first question:
- Identify the loaded product node and its
context/— if it does not exist, it is created with this interview. - Read in full the files that
context/already has. This is incremental: it is completed in stages and a filled section is never overwritten without saying so first. - Read the context of the owning organization and, if it exists, the dated research that applies —
it lives in the
research/of the node, next tocontext/. - Tell the operator what you read and which sections you can already fill on your own with that. Only then does the interview start, and only over what is missing — you do not ask them what the system already has written.
Phase 2 — The interview
The questions come in rounds, as .agents/skills/grill/SKILL.md#method defines them, each with a line about
why that section changes a decision. Without that line the question sounds like bureaucracy.
The six questions that force the truth
Opportunity and business stage, before touching the solution:
- What is the strongest evidence that someone wants this? Not interest: behavior.
- What do they solve it with today? If the answer is "with nothing", why do they live fine without this?
- Name me a concrete person. Their job title, and what happens to them if they do not solve it.
- What is the smallest version someone would pay for this week?
- What surprised you watching someone use it or try to solve it?
- In three years, does this become more necessary or less?
Research stage
Conclusions are not invented: if no research has been done, that is said and the matching discovery tool is offered. Questions cover the segment, the explicit non-target, and the alternatives the operator already uses today.
Solution stage
Before talking about what to build, the premise is challenged: is this the right problem? what happens if nothing is done? is there something already built that would do? Only then: vision, slicing, what it does NOT do with its reactivation condition, hard constraints, assumptions with their invalidation condition.
How to apply pressure
The method of .agents/skills/grill/SKILL.md#method decides when to counter-question, how many rounds, and
what to do with the second resistance. It is not repeated here: it is applied.
Alternatives phase, mandatory
Before fixing the solution, 2 or 3 paths are presented, each with its effort, risk and what it reuses of what already exists:
- the smallest shippable one — the smallest version that can be launched this week,
- the one that ages best — the one that demands the least rework if the product grows,
- a lateral one that reframes the problem — a way out that is not "more of the same, smaller".
The operator picks one. Without this phase the document records the first idea, not the best one.
The explicit-gap rule
A gap is written only when the operator explicitly decides not to answer, and always with who closes it. A file full of gaps is not a deliverable: it is a failure dressed up as completeness. If a gap appears because the section was never asked about, it is not a gap: it is work not done, and the interview resumes.
Show before writing
Before touching any file, the operator is shown exactly what is going to be written —the content, not a summary— and their go-ahead is awaited. Only the files the interview touched get written; the ones that were already complete are not overwritten. A glossary term the operator accepted with "yes" in a round was already shown with its exact text: it is written then, as the method says, and is not shown again.
The closing verdict
At the end, one of three, always explicit:
- Complete — enough to write specs.
- Complete with reservations — it is possible to move forward, and these are the open questions that remain.
- Missing context — which file was left unclosed and what it takes to close it.
The minimums gate: if glossary.md, scope.md or the architecture of the body are left empty,
no specs come out of there yet. It is said explicitly, never left to be discovered later.
Destination
The skill resolves the destination before producing the deliverable, never after. Three cases, two destinations:
- A product node is loaded: the deliverable goes to
research/<YYYY-MM-DD>-<name>.mdof that node. - There is a brain, but no product node — no workspace yet, or a workspace without one: the deliverable is written to a file in the current folder.
- There is no brain at all: the deliverable is written to a file in the current folder.
With no product node, the file is written to the current folder anyway. The closing message names only the path it just wrote and stops there — that is the normal way this skill ends, not an anomaly to qualify.
This skill never asks which destination to use, and it never invents a third one.
The rest of the pack installs one skill at a time. Look at .agents/skills/ first and then .claude/skills/ (a skill present in both
counts once) and offer only the ones that are not there — once per session: the first time this skill closes in the session,
never again on a later close of the same or another deliverable:
grill—npx skills add pedroromeroluna/ai-first-product-skills --skill grill
The whole pack at once: npx skills add pedroromeroluna/ai-first-product-skills. That command installs what the pack offers;
anything listed above it is installed by naming it.
Does it work?
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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.
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