j.evaluate
Skill0 starsChanged 21 days agoApache-2.0View on GitHub
Analyzes example files against a target goal and produces a structured evaluation rapport.
In this repository151 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- j.brainstormSkill
- j.breakSkill
- j.btwSkill
- j.check-inSkill
- j.clearifySkill
- j.close-storySkill
- j.cloud-connectSkill
- j.commitSkill
- j.connectSkill
- j.continueSkill
- j.conventionsSkill
- j.dashboard-shareSkill
- j.dashboardSkill
- j.deep-diveSkill
- j.distributeSkill
- j.docSkill
- j.doc-syncSkill
- j.doooSkill
- j.doSkill
- j.jenga-configSkill
- j.jenga-permission-levelSkill
- j.jengaSkill
- j.errorSkill
- j.examplifySkill
- j.gitignoreSkill
- j.helpSkill
- j.ideaSkill
- j.improveSkill
- j.initSkill
- j.jbpSkill
- j.lgtmSkill
- j.pi-planSkill
- j.playbook-newSkill
- j.playbookSkill
- j.proceedSkill
- j.publishSkill
- j.reconcile-originSkill
- j.reconcileSkill
- j.redoSkill
- j.skillifySkill
- j.smoke-testSkill
- j.spinoffSkill
- j.statusSkill
- j.testSkill
- j.todoSkill
- j.toolsSkill
- j.unchartedSkill
- j.wtfSkill
- skill-nameSkill
- j.brainstormSkill
- j.breakSkill
- j.btwSkill
- j.check-inSkill
- j.clearifySkill
- j.close-storySkill
- j.cloud-connectSkill
- j.commitSkill
- j.connectSkill
- The first 60 shown.
The file
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
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 36
Use a simple 1–5 scale with a one-line justification.
≈ “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
Evaluate
skills/j-evaluate/ is the canonical, hand-edited directory for this skill, per CLAUDE.md's "The Canonical Naming Contract" (the E50 reopening of 2026-09-09, which promoted skills/j-evaluate/ from generated twin to sole canonical form). The j- prefix is there for collision safety — a real directory under a distinct name, so a host tool shipping its own same-named built-in command cannot shadow it (Claude Code's native skill resolution is a literal-string, directory-name-based match; see project/documentation/skill-authoring.md's "Invocation Convention").
⚠️
scripts/generate-j-alias.shwas retired byE50_S14and no longer exists — there is nothing to run. This file was previously generated from a bareskills/evaluate/SKILL.mdsource;E50_S15deleted that directory. This file is now the sole canonical, hand-edited source for this skill — edit it directly.
Input
Expects a filled eval_invokation_template.yml with:
goal: the confirmed target goalpaths: list of example files from/examplifyto analyze
Steps
1. Read Input
Parse the provided YAML file. If goal is empty or paths is empty/missing,
stop and ask the user to fill in the missing fields before proceeding.
2. Read Example Files
Load each file listed under paths. These are outputs from /examplify and
represent real observed behavior in the codebase.
3. Analyze Against Goal
For each example file, evaluate:
- Qualitative observations: What is the current behavior? How does it relate to the goal?
- Gaps and issues: What is missing, broken, or misaligned relative to the goal?
- Score: How well does the current behavior satisfy the goal? Use a simple 1–5 scale with a one-line justification.
4. Synthesize
Across all examples, identify:
- Recurring patterns or systemic issues
- The most critical gaps blocking the goal
- Any areas that are already well-aligned
5. Write Rapport
Copy evaluation_rapport_template.md. Derive the rapport filename from the goal in kebab-case:
<target-goal-in-kebab-case>-eval.md
Fill in the rapport based on the template structure and save to project/rapports/analysis/ with this structure.
6. Return
Return the rapport filename to the caller (e.g. /improve).
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.