project-development-mindset
Skill68 starsChanged 7 months agoApache-2.0View on GitHub
Plan and carry repository changes through implementation, verification, and handoff. Use only when the user invokes this skill by name; ordinary repository changes proceed without it.
In this repository16 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- agents-md-generatorSkill
- brainstorm-firstSkill
- debugging-workflowSkill
- design-system-generatorSkill
- docker-local-devSkill
- documentation-guidelinesSkill
- laravel-11-12-app-guidelinesSkill
- laravel-13-app-guidelinesSkill
- office-web-ui-systemSkill
- performance-optimizationSkill
- run-reviewable-subtask-loopSkill
- testing-verificationSkill
- ui-ux-concept-implementationSkill
- vps-docker-traefik-deploySkill
The file
We split this skill into the rules it gives an agent
6 rules. About 0 are common, 6 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈6
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 13
Run in the main conversation by default.
- Distinctive: line 20
Keep the original objective and accepted changes in view during long work.
- Distinctive: line 25
Keep abstractions tied to current invariants or meaningful reuse.
- Distinctive: line 27
Use installed versions and official documentation for uncertain external APIs.
- Distinctive: line 33
Add regression coverage when it protects meaningful behavior.
- Distinctive: line 37
Update durable documentation when behavior, setup, commands, ownership, or contracts change.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Project Development Mindset
Deliver the requested outcome using project evidence and the smallest coherent change. Scale investigation and verification to impact, uncertainty, and reversibility.
Delegation
Run in the main conversation by default. Delegation can increase usage: obtain explicit approval for the proposed agent count and scope before using subagents. Reuse that approval within its bounds; ask again before expanding the approved count or scope.
Establish the task
- Inspect applicable instructions, Git state, and the source, tests, configuration, and docs relevant to the request. Preserve unrelated user work and follow the repository's branch and freshness policy.
- Identify observable success criteria and affected contracts. Plan in proportion to dependencies and uncertainty.
- Distinguish intended behavior from current behavior. Resolve stale or conflicting docs against source and runtime evidence; ask only when the remaining choice belongs to the user.
- Keep the original objective and accepted changes in view during long work. A status question or correction usually steers the task rather than replacing it.
Implement
- Reuse project components, dependencies, commands, and architecture when their semantics fit. Change a harmful pattern only where it affects this task.
- Keep abstractions tied to current invariants or meaningful reuse. Avoid speculative options, new frameworks, and adjacent cleanup without a present need.
- Inspect affected callers and consumers when changing public APIs, persisted data, permissions, or cross-project contracts.
- Use installed versions and official documentation for uncertain external APIs. Keep credentials out of source, logs, fixtures, and output.
- Carry authorized work through to completion. Prepare a concrete, reviewable result before requesting any still-missing approval for publication, deployment, or other consequential actions. Do not infer those actions from an ordinary implementation request.
Verify and review
- Choose checks that can detect failures in the changed behavior, using the project's existing tools. Complete required checks and follow any explicit testing budget.
- Add regression coverage when it protects meaningful behavior. Skip tests that merely duplicate a reversible, low-impact edit.
- Reuse passing evidence for unchanged code and equivalent environments. Expand or repeat checks for new changes, failures, affected contracts, or unresolved risks; stop once the evidence is sufficient. Offer a broader suite only when it would resolve a concrete gap, respecting repository approval requirements.
- For material UI changes, inspect the rendered result at relevant states and viewports under the host's browser policy. Distinguish manual browser evidence from automated E2E tests.
- Review the complete task diff against the intended base for missing requirements, regressions, unsafe changes, and accidental files. Fix actionable findings and rerun affected checks.
- Update durable documentation when behavior, setup, commands, ownership, or contracts change. Use existing owners instead of creating new documentation structures for routine work.
Use specialist guidance selectively
Routine tests, docs edits, framework commands, and browser checks stay part of implementation. Bring in a specialist skill when its domain is the main difficulty of the current step.
Read quality-skill-routing.md when choosing a specialist would help, or ui-ux-concept-routing.md for visual decisions and reference matching. Load only relevant guidance, avoid running two workflows for the same responsibility, and let go of a phase's instructions once the task moves on. An unavailable optional skill should not block work the current tools can complete.
run-reviewable-subtask-loop is the user's to invoke; task size and internal subtasks neither activate it nor authorize subagents.
Handoff
Lead with what changed and why. Report relevant checks and their results, remaining gaps, and any decision still needed. Compare the delivered behavior with the user's criteria; fix in-scope gaps before stopping. Describe remaining uncertainty through the evidence behind it.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
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.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

