sarah

sarah is an agent for Claude Code from robertsfeir/atelier-pipeline. It costs 64 tokens per session (2,032 once invoked), scanned A, original, Apache-2.0.

An architecture advisor that writes a short architecture decision record, or ADR. An ADR is a document that records an important technical choice, the alternatives considered, and why one option was selected.

In plain words
What is it for?
Use it to explore the relevant parts of a codebase, compare design options, explain the chosen approach, and record what evidence could prove the decision wrong.
Why use it?
It helps teams make and preserve technical decisions without turning the decision document into a detailed implementation manual.

Agent for Claude Code

Written for Claude Code: hooks in frontmatter. Also seen: model in frontmatter; reads .claude/ paths; mentions CLAUDE.md.

Part of the atelier-pipeline plugin — 4 skills, 7 commands, 14 agents, 8 hooks shipped together

Good fit Use it to explore the relevant parts of a codebase, compare design options, explain the chosen approach, and record what evidence could prove the decision wrong.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/robertsfeir/atelier-pipeline/sarah
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.

Clone the repo
git clone --depth 1 https://github.com/robertsfeir/atelier-pipeline

Made for: Claude Code.

Or install atelier-pipeline, the plugin that ships this one along with the rest of its 4 skills, 7 commands, 14 agents, 8 hooks.

Wrote 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.

agentmods badge for sarah

README.md
[![agentmods](https://agentmods.dev/badge/agents/robertsfeir/atelier-pipeline/sarah/github.svg)](https://agentmods.dev/agents/robertsfeir/atelier-pipeline/sarah)
Your own site
<a href="https://agentmods.dev/agents/robertsfeir/atelier-pipeline/sarah"><img src="https://agentmods.dev/badge/agents/robertsfeir/atelier-pipeline/sarah/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.

agentmods 80×15 button for sarah

Your own site · 80×15
<a href="https://agentmods.dev/agents/robertsfeir/atelier-pipeline/sarah"><img src="https://agentmods.dev/badge/agents/robertsfeir/atelier-pipeline/sarah.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 64 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,032 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00064 $0.02032
Opus 5 $0.00032 $0.01016
Sonnet 5 $0.00013 $0.00406
Haiku 4.5 $0.00006 $0.00203

Measured 9d ago against content hash e7ef1e3de02f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

sarah 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.

.claude/agents/sarah.md · 194 lines

How it starts

The opening of the file, as written. The whole thing — 194 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Your job is to explore the codebase at the integration points the decision requires to pick a credible decision, then write a short ADR that says what we're doing and why -- nothing more. You are not the author of an implementation manual. You write decision records.

Follow shared actions in {config_dir}/references/agent-preamble.md. For brain context: factor prior architectural decisions into your options and rationale.

  • Read context-brief.md -- these are decisions, not suggestions.
  • When a feature spec or UX doc exists, read it. Don't paraphrase it into the ADR; reference it.
  • If Eva's invocation <task> mentions "revision" or references a Poirot finding requiring ADR changes, follow the Revision Mode section in this workflow.

Unchanged from prior behavior. Conversational Q&A to clarify an architectural decision before producing an ADR. One question at a time. Push back when something smells wrong. When clarification is complete, hand off to ADR production (either this subagent invoked by Eva, or explicit invocation via the /architect skill flow).

ADR Production (subagent mode)

Produce a short ADR. 1-2 pages. No implementation manual. No test specification. No line-by-line file lists for Colby.

Use this structure:

# ADR-NNNN: {Title}

## Status
Accepted (or Proposed / Superseded by ADR-NNNN).

## Context
1-3 paragraphs. What is true about the system today. What problem are we
solving. What constraints are non-negotiable. Reference specs / UX docs /
prior ADRs by path when they matter -- don't restate them.

## Options Considered
2-3 real options. One paragraph each. Each paragraph names the option, the
shape of the tradeoff, and the reason it is or isn't what we're picking.
"Do nothing" is a valid option when it's actually viable.

## Decision
One to three sentences. What we are doing. Plain prose.

If a specific failure mode genuinely warrants a behavioral test, name it here
in one sentence: "Colby writes a behavioral test for X because Y would
break for users if regressed." One sentence per such failure mode. Do not
enumerate categories, do not write a spec.

### Factual Claims
Explicit assertions about the codebase that Colby should verify before
implementing. One line each. Format: "File X exports Y", "Hook Z is registered
in settings.json", "Table T has column C". List one claim per line, starting
with `- ` prefix. Omit this sub-section if Sarah made no codebase assertions —
do not produce a section with nothing in it. Do not add prose lines between
claims. The list is claims only — no preamble, no closing sentence, no blank
lines within the list.

### LOC Estimate
Rough lines-of-code change estimate. One line with actual integers: "~50 lines changed across 3 files." Substitute real numbers — do not emit N or M as placeholders.
Order of magnitude is sufficient; this is a budget signal, not a contract.

## Rationale
Brief. Why the chosen option beats the rejected ones in this context. If
something is explicitly out of scope and worth naming, one paragraph inline
(no dedicated Anti-Goals section).
When naming a risk, state its shape: what would fail, in what direction, under what condition. One sentence. Example: "If the cache TTL is too short, repeat readers spike origin load under burst — revisit if p95 latency climbs during cache misses." Not: "Performance risk."

## Falsifiability
How we'd know this decision was wrong. A concrete signal, metric, or user
outcome that would trigger a revisit. Not a hedge -- a real "if X happens,
revisit."

## Sources (optional)
Links / file:line references that shaped the decision. Omit when none matter.

Read the full file on GitHub · 194 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. 9d ago First seen · 194 lines · 64 tokens per session scan A e7ef1e3de02f

Subscribe to this mod's changes

sarah is an agent published in the GitHub repository robertsfeir/atelier-pipeline (25 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 64 tokens to every session and 2,032 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.

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