agentleFS
moazessam376-devmoazessam376-dev/sparring/skill/SKILL.md

sparring

Skill0 starsChanged 2 months agoMITView on GitHub

Teach an engineer to defend an agent-built repository through a verified survey, a catalogue-backed lesson, and one-question-at-a-time drills.

6 other projects use a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

1 rule. 0 are common, 1 is distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 6 edited versions we read keep these.

  • 1

    Distinctive

    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
  1. Distinctive:

    Use this skill when the user asks for a repository survey, project map, lesson, drill, mock interview, or grade review.

    line 8

“Common” is measured: kept by at least 6 in 10 of the 6 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.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Sparring

Use this skill when the user asks for a repository survey, project map, lesson, drill, mock interview, or grade review. Make the learner retrieve and defend the code instead of outsourcing the explanation to the agent. Evidence: docs/research/2026-09-10-learning-science.md, findings 1, 8, and 9.

Select a mode

User requestModeRead next
Survey a repository, make a project map, or start a projectsurveyreferences/survey.md
Teach a project, topic, or drill gaplessonreferences/lesson.md
Drill, quiz, test, or run spaced reviewdrillreferences/drill.md

Load references/interviewer-rules.md for every mode. Load references/components.md before authoring a lesson. Load only the references required by the selected mode.

Working contract

  1. Build a verified repository map before writing a deep lesson. Keep coverage boundaries visible and preserve claim provenance. Evidence: docs/research/2026-09-12-large-repository-survey.md, findings 1, 9, 10, and 11.
  2. Assemble lessons from the closed component catalogue. Supply field content; let the application own layout, interaction, and grading. Evidence: docs/2026-09-12-sparring-as-software-design.md, sections 3.1 and 4; docs/research/2026-09-10-learning-science.md, findings 5, 6, and 9.
  3. Make the learner commit an answer before revealing a rubric or grounding. Ask one question at a time and record every attempt. Evidence: docs/research/2026-09-10-learning-science.md, findings 1, 8, 9, and 11.

The connected server owns the due queue, rubrics, records, contests, projects, topics, cards, lessons, and survey submissions. The reference files name the server tools and their order.

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People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
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What did you use it for? e.g. Reviewing pull requests in a Rails app

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.