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software-factory

Shared language for designing a software factory: the tasks it runs and the services it plugs into.

Install / Use

npx skills add mattpocock/skills --skill software-factory

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

84/100

Category

Operations

Supported Platforms

Universal

Our assessment of software-factory

software-factory scores 84/100 on our quality scale, 561st of 757 Operations skills we index.

Its SKILL.md is 5.9 KB long, split into 6 sections and no code examples: a solid amount of guidance for an agent.

With 268,790 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
26/30
Structure
11/20
Description
12/15
Adoption
20/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 37 days ago, so software-factory is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

software-factory compared with similar skills

All 4 of these similar skills score higher than software-factory; compare them before choosing.

SkillScoreStarsUpdatedFormat
software-factory (this skill)by mattpocock84268.8k37d agoSKILL.md
taste-skillby Leonxlnx100106.6ktodayCLAUDE.md
algorithmic-artby anthropics100177.9k39d agoSKILL.md
pptxby anthropics100177.9k39d agoSKILL.md
designby nextlevelbuilder100137.2k16d agoSKILL.md

Frequently asked questions

How do I install software-factory?
Run npx skills add mattpocock/skills --skill software-factory. The install tabs above show the steps for each supported agent.
Which AI agents does software-factory work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is software-factory safe to use?
It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is software-factory still maintained?
The repository was last updated 37 days ago, so software-factory is actively maintained.

name: software-factory description: Shared language for designing a software factory: the tasks it runs and the services it plugs into. disable-model-invocation: true

A software factory is a system of agents that turns tickets, PRs and schedules into merged code, deployed on remote infrastructure the user chooses. This skill is the language for designing one. Use these terms, and only these, when discussing or whiteboarding a factory; when the user reaches for a word under Avoid, name the canonical term.

Tasks and runs

Task: A kind of work the factory performs, defined once and run many times: review, explore, implement, ratchet. A task may work on a ticket, a PR, or the codebase as a whole. Avoid: job, workflow, action

Trigger: The event that starts a run: a change in the ticket tracker or git host, a clock in the orchestrator, or another run.

Run: One execution of a task on one runner, from its trigger to its finish, treated as a black box. A run triggers further runs either directly, through logic in the orchestrator, or by changing the ticket tracker or git host. A run never waits for a human: it ends, and the human's later change to the ticket tracker or git host triggers a new run. Avoid: session

Runner: The disposable machine a run executes on. Nothing on it survives the run, even when the machine itself is long-lived: a run's only memory of earlier runs is the ticket tracker, the git host and the orchestrator. Avoid: server, host, box, compute, sandbox

Services

Ticket tracker: Where tickets live, and the factory's human interface: humans schedule work by filing tickets, talk to agents in their comments, and their changes to tickets trigger runs. Avoid: issue tracker, ticket manager, project board

Ticket source: Anything outside the factory that creates tickets in the ticket tracker: a feedback button, a monitor, an error tracker, an inbox. Avoid: data source, trigger source, intake

Git host: Where branches, PRs and reviews live. Avoid: code host, forge, repo

Orchestrator: The component that receives triggers, starts runs on runners, and records which runs are queued, in flight or finished. Avoid: dispatcher, scheduler, control plane

Observability platform: Where runners send logs, traces and status, so a human can see what happened inside each run. Optional: the product filling the runner or orchestrator slot often shows enough on its own. A run never decides on it until something writes it into the ticket tracker or git host. Avoid: observability, logs, monitoring, dashboard

Designing a factory

A design has two halves: the services, each a slot filled with a product, and the tasks whose runs move work through them.

Start from the user's problem, not the factory: untriaged tickets, PRs waiting for automated review, a stricter automated check to migrate to, bugs nobody reads. When the user names a problem or doesn't know what to build, read EXAMPLE-TASKS.md for the tasks that solve common ones.

Start slow

Every trigger is an accelerator. Accelerators without brakes make a slop cannon. There are three brakes:

  • Automated checks: deterministic gates (types, lint, tests) that every run must pass.
  • Automated review: a separate run that reads the diff cold against the codebase's standards and the ticket, when there is one.
  • Human review: a human reads the PR before it merges; what it catches becomes new automated checks and sharper automated review.

Add one automated trigger at a time, throttled at first (one bug report in ten, a clock once a day), with human review on every PR. Open the throttle as the brakes earn trust, and cap every loop of runs at a few tries before a human.

Fill every slot

Each service is a slot. One product can fill several slots, and one server can host several services. Three designs, side by side:

| Service | All on GitHub | Linear tickets | Own tracker | | ---------------------- | ------------------------------- | ------------------------------ | ------------------------ | | Ticket tracker | GitHub Issues | Linear | own app | | Ticket source | feedback button | feedback button, monitor | feedback button, monitor | | Git host | GitHub | GitHub | GitHub | | Orchestrator | GitHub Actions | own server + database | own app | | Runner | Actions runner | Actions, E2B, Daytona or a VPS | own app, or sandboxes | | Observability platform | none: Actions run pages suffice | an LLM tracing platform | own app |

When the user is choosing a product for a slot, read that slot's survey to get oriented, then research the current options yourself; each survey groups the options by type and lists the questions that decide the slot:

Buy the services and build the tasks: the tasks carry the user's design, the services are generic. Favour an off-the-shelf ticket tracker: it is robust, people already know it, and outside users are easy to let in.

Question every task

For each task, answer:

  1. What triggers it?
  2. What does it do, and which services does it read and write?
  3. What does it trigger next?
  4. Where does a human re-enter?
  5. What stops two runs doing the same work?

For each ticket source, answer: what stops it filing the same ticket twice?

A design is finished when every slot names a product (or, for the observability platform, a deliberate none) and every task and ticket source has an answer to every question.

Related Skills

View on GitHub
GitHub Stars268.8k
CategoryOperations
Updated1mo ago
Forks22.7k

Languages

Shell

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions
software-factory — Universal Skill: Install & Safety Check | SkillAgent