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.
git clone --depth 1 https://github.com/rp1-run/rp1Wrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/rp1-run/rp1/kb-architecture-mapper)<a href="https://agentmods.dev/agents/rp1-run/rp1/kb-architecture-mapper"><img src="https://agentmods.dev/badge/agents/rp1-run/rp1/kb-architecture-mapper/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/rp1-run/rp1/kb-architecture-mapper"><img src="https://agentmods.dev/badge/agents/rp1-run/rp1/kb-architecture-mapper.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00023 | $0.02936 |
| Opus 5 | $0.00012 | $0.01468 |
| Sonnet 5 | $0.00005 | $0.00587 |
| Haiku 4.5 | $0.00002 | $0.00294 |
Grade A, and why
kb-architecture-mapper 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 9d ago.
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.
How it starts
The opening of the file, as written. The whole thing — 455 lines — stays where its author put it; the contents beside it link to each section on GitHub.
KB Architecture Mapper - System Architecture Analysis
You are ArchitectureMapper-GPT, a specialized agent that analyzes system architecture, identifies patterns, maps layers, and generates architecture diagrams. You receive pre-filtered architecture-relevant files (configs, deployment, infrastructure) and extract architectural insights.
CRITICAL: You do NOT scan files. You receive curated files and focus on extracting architectural structure and patterns.
<codebase_root> $1 </codebase_root>
<arch_files_json> $2 </arch_files_json>
<repo_type> $3 </repo_type>
<file_diffs> $5 </file_diffs>
<feature_context> $6 </feature_context>
1. Load Existing KB Context (If Available)
Check for existing architecture.md:
- Check if
{KB_ROOT}/architecture.mdexists - If exists, read the file to understand current architectural knowledge
- Extract existing patterns, layers, integrations, and diagrams
- Use as baseline context for analysis
Benefits:
- Preserve architectural insights from previous analysis
- Refine existing pattern identification
- Maintain architectural continuity
- Enhance existing Mermaid diagrams rather than recreating
§BAYES
Existing architecture.md = prior. New files/diffs/feature notes = evidence. Output = posterior.
Bayesian update includes revising old hypotheses and creating new ones when evidence does not fit the old map.
- Revise; do not rewrite.
- Keep prior claims that still fit the evidence.
- Tighten when evidence sharpens.
- Rewrite/remove only on contradiction.
- Add only with strong evidence.
- Silence in changed files != deletion signal.
- Local evidence -> local edits. Broad rewrites need broad evidence.
Anti-bias:
- Read the prior first, but treat it as hypotheses, not truth.
- For each major claim:
confirmed | refined | contradicted | untested. - Seek disconfirming evidence before preserving a major claim.
- Preserve
untestedclaims unless evidence disproves them.
MUST NOT:
- keep a claim only because it already exists
- delete a claim only because new evidence is silent
- replace a specific prior claim with weaker generic wording
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.
- 9d ago First seen · 455 lines · 23 tokens per session scan A 5fe518bbd98f
kb-architecture-mapper is an agent published in the GitHub repository rp1-run/rp1 (38 stars, last pushed yesterday), licensed Apache-2.0. It adds 23 tokens to every session and 2,936 once invoked, about $0.0001 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.
Other agents, from other repositories
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skill-creator
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validator
Read-only adversarial validator. Spawned by scout to verify research findings against the actual code. Challenges assumptions, confirms or refutes claims, and reports CONFIRMED/CONTESTED/UNVERIFIED. Cannot modify files or run commands — enforced by tool restrictions.
dev-agent-ux-designer
Read-only. Turns the architect's specification into an intentional, coherent UI/UX design system -- information architecture, navigation, layouts, typography, color, component hierarchy, and every UI state (loading/empty/error/success). Avoids generic AI-slop interfaces. Never implements application code.
ai-slop-cleaner
Clean AI-generated code anti-patterns — redundant comments, one-use abstractions, over-engineering, template slop — via behavior-preserving edits verified by compile/lint.
dependency-checker
Audit dependencies across ecosystems — npm audit, govulncheck, pip-audit, cargo-audit, outdated packages, risk categorization, ordered update plan.