Agent skill

ride

Analyze codebase to extract reality into Loa artifacts

majiayu000534★ · 1 repos on radarProfile →
claude-coderead-onlyMIT
Install
npx skills add majiayu000/claude-skill-registry --skill riding-codebase-0xhoneyjar-loa-beauvoir --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 52 KB
Bundled scripts: none
Allowed tools: ReadGrepGlobBash(git*)
Path: skills/analysis/riding-codebase-0xhoneyjar-loa-beauvoir/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

Review
written from the skill's own SKILL.md · Aug 5, 2026

What it does

The skill directs an agent to ride through a codebase to produce evidence-grounded Loa artifacts. It emphasizes verifying code against claims with file:line citations, flagging issues rather than fixing, and ensuring the grimoire mirrors the code. It outlines a structured workflow from preflight checks, integrity verification, and context discovery to interactive interviews and generating verification claims, all while logging progress to a trajectory file.

How it works

  • Preflight & Mount Verification: checks for a mounted Loa version file, then performs system integrity checks against a checksums file, blocking Ride unless integrity is verified or overridden with --force-restore. It also detects the execution context (framework repo vs. target repo).
  • Target Resolution (framework repo only): prompts for a codebase target when running from the Loa framework repository.
  • Initialize Ride Trajectory: records a preflight entry in a trajectory JSONL file.
  • Codebase Probing and Loading Plan: runs a probe to determine total files, lines, and estimated tokens; selects a loading strategy (full, prioritized, or excerpts) based on size; generates a loading plan and logs the probe to trajectory.
  • Phase 1: Interactive Context Discovery: checks for existing context, prompts to add context files, analyzes any provided context, and conducts a gap-focused interview using a structured topic list.
  • Generate Claims to Verify: mandatory step to create grimoires/loa/context/claims-to-verify.md with a markdown table for architecture, domain, tribal knowledge, and WIP status, including verification strategies. Logs the activity to trajectory.

When to use it

  • Use when you need to extract or verify truth from a codebase, producing Loa artifacts that reference exact file:line citations. Activate when starting a project analysis to ensure evidence-backed documentation and flag potential issues rather than attempting fixes.

What it can touch

  • Repository files and directories related to the Loa workflow and target codebase, including:
    • .loa-version.json
    • .claude/checksums.json
    • grimoires/loa/a2a/trajectory/
    • grimoires/loa/reality/
    • grimoires/loa/context/
    • target codebase directories detected via TARGET_REPO
  • Tools invoked: Read, Grep, Glob, Bash(git *) as per allowed-tools.

Caveats

  • Requires the Loa to be mounted and integrity file to exist for blocking behavior; otherwise blocks on integrity or FORCE RESTORE are explicit in the script.
  • The workflow emphasizes flagging issues and evidence-backed claims; it does not perform code fixes.
  • Output includes prompts and interactive questions that depend on user responses (e.g., target repo selection, context file prompts).
From the SKILL.md

# Riding Through the Codebase You are analyzing an existing codebase to generate evidence-grounded Loa artifacts following the v0.6.0 Enterprise-Grade Managed Scaffolding model. > *"The Loa rides through the code, channeling truth into the grimoire."* ## Core Principles ``` CODE IS TRUTH → Loa channels CODE → Grimoire reflects REALITY ``` 1. **Never trust documentation** - Verify everything against code 2. **Flag, don't fix** - Dead code/issues flagged for human decision 3. **Evidence required** - Every claim needs `file:line` citation 4. **Target repo awareness** - Grimoire lives WITH the code it documents --- ## Phase 0: Preflight & Mount Verification ### 0.1 Verify Loa is Mounted ```bash if [[ ! -f ".loa-version.json" ]]; then echo "❌ Loa not mounted on this repository" echo "" echo "The Loa must mount before it can ride." echo "Run '/mount' first, or:" echo " curl -fsSL https://raw.githubusercontent.com/0xHoneyJar/loa/main/.claude/scripts/mount-loa.sh | bash" exit 1 fi VERSION=$(jq -r '.framework_version' .loa-version.json) echo "✓ Loa mounted (v$VERSION)" ``` ### 0.2 System Zone Integrity Check (BLOCKING) Before the Loa can ride, verify the System Zone hasn't been tampered wit

What's inside
Steps it walks through
  1. Core Principles
  2. Phase 0: Preflight & Mount Verification
  3. 0.1 Verify Loa is Mounted
  4. 0.2 System Zone Integrity Check (BLOCKING)
  5. 0.3 Detect Execution Context
  6. 0.4 Target Resolution (Framework Repo Only)
  7. 0.5 Initialize Ride Trajectory
  8. Attention Budget
  9. Token Thresholds
  10. Clearing Triggers for Codebase Riding
  11. 4-Step Clearing
  12. RLM Pattern Alignment
  13. Semantic Decay Stages
  14. Phase 0.5: Codebase Probing (RLM Pattern)
Ships with 1 file
  • metadata.json
Commands it runs
if [[ ! -f ".loa-version.json" ]]; then
echo "❌ Loa not mounted on this repository"
echo ""
echo "The Loa must mount before it can ride."
echo "Run '/mount' first, or:"
echo "  curl -fsSL https://raw.githubusercontent.com/0xHoneyJar/loa/main/.claude/scripts/mount-loa.sh | bash"
exit 1
fi
echo "✓ Loa mounted (v$VERSION)"
if [[ ! -f "$CHECKSUMS_FILE" ]]; then
More from claude-skill-registry
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About this skill
What does the ride skill do?

Analyze codebase to extract reality into Loa artifacts

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill riding-codebase-0xhoneyjar-loa-beauvoir --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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