agentmods.dev

bootstrap

A startup workflow for scanning a repository and saving a baseline, meaning a reference snapshot of its structure and health. It also prepares that information for follow-up analysis.

In plain words
What is it for?
Beginning coding sessions, checking repository health, recording structural metrics, and finding the most important hotspots and failing rules.
Why use it?
It gives later coding work a clear before-state and highlights files or rules that may cause problems before edits begin.

Skill for Claude CodeCodex

11 3mo ago A scan 52 tokens original MIT
View the source file RayforceDB/raysense
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/rayforcedb/raysense/bootstrap
Any agent
npx skills add RayforceDB/raysense --skill bootstrap
Clone the repo
git clone --depth 1 https://github.com/RayforceDB/raysense

Made for: Claude Code, Codex.

Per session 52 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 665 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00052 $0.00665
Opus 5 $0.00026 $0.00332
Sonnet 5 $0.00010 $0.00133
Haiku 4.5 $0.00005 $0.00067

Measured yesterday against content hash 0fb8e0b0ea95, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

bootstrap scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

claude-plugin/skills/bootstrap/SKILL.md · 64 lines

How it starts

The opening of the file, as written. The whole thing — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Bootstrap

Run this once per session, before any non-trivial edits. It produces a persisted baseline plus live splayed-table memory that the other raysense skills (impact, verify, audit) read against.

All tools take a path argument. Always pass the current working directory as an absolute path so per-project state stays inside the repo (<repo>/.raysense/).

Steps

  1. Health overview — call raysense_health with path: <cwd>. Note the overall grade and the worst dimension.
  2. Save the baseline — call raysense_baseline_save with path: <cwd>. This writes <cwd>/.raysense/baseline/manifest.json plus splayed tables under <cwd>/.raysense/baseline/tables/.
  3. Confirm memory is live — call raysense_memory_summary with path: <cwd>. Report the row/column counts so the user can see the memory is materialized.
  4. Surface the top 3 hotspots — call raysense_hotspots and raysense_rules. List the three highest-traffic files and any already-failing rules. These are the spots most likely to bite during the session.

What to keep in working memory

After bootstrap, the agent should remember (briefly):

  • The overall health grade and the lowest-scoring dimension.
  • The three hottest files (high coupling × high churn).
  • Whether any rules are currently failing (so a later regression isn't mistaken for pre-existing breakage).

When to skip

  • Session is read-only (the user just asked a question -- no edits planned). Skip bootstrap; reach for audit instead if structural context is needed.
  • A baseline already exists from a recent session and no commits have landed since (git log -1 --since='1 hour ago' shows nothing). Re-using the previous baseline is fine; just call raysense_health for a fresh grade and skip the rest.

See also

The baseline this skill produces is queryable, not just a dump. After bootstrap, the agent has access to:

  • raysense_baseline_query -- run any Rayfall expression against a saved table. Syntax and worked examples in the query skill (select / .graph.* / Datalog / vector search).
  • raysense_policy_check -- evaluate .rfl policy packs in <repo>/.raysense/policies/; ships its own exit-code semantics for CI gating.
  • raysense_baseline_import_csv -- bring external CSVs (coverage, lint counts, embeddings) into the baseline as queryable tables.

Read the full file on GitHub · 64 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 64 lines · 52 tokens per session scan A 0fb8e0b0ea95

Subscribe to this mod's changes

bootstrap is a skill published in the GitHub repository RayforceDB/raysense (11 stars, last pushed 3mo ago), licensed MIT. It adds 52 tokens to every session and 665 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Analytics and metricsCode reviewMemory and contextai-agentsclaude-agentclaude-codecode-architecturecode-qualitydependency-graph
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