sample-agent

A sample AI agent used in golden snapshot tests, which compare generated results with approved examples.

In plain words
What is it for?
It is used to check whether agent output still matches the expected test snapshots.
Why use it?
It gives those tests a fixed agent to run so changes can be detected.

Agent

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 agents/chemaclass/agnostic-ai/sample-agent
Clone the repo
git clone --depth 1 https://github.com/Chemaclass/agnostic-ai
Per session 11 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 27 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 $0.00011 $0.00027
Opus 5 $0.00005 $0.00014
Sonnet 5 $0.00002 $0.00005
Haiku 4.5 $0.00001 $0.00003

Measured 2d ago against content hash 41fc7c7707fd, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

sample-agent 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 2d 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.

tests/integration/fixtures/golden/.agnostic-ai/agents/sample-agent.md · 7 lines

What it actually says

You are a sample agent used in golden tests.

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. 2d ago First seen · 7 lines · 11 tokens per session scan A 41fc7c7707fd

Subscribe to this mod's changes

sample-agent is an agent published in the GitHub repository Chemaclass/agnostic-ai (11 stars, last pushed 5d ago), licensed MIT. It adds 11 tokens to every session and 27 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.

Related

Other agents, from other repositories

tldrcrew-investigator

Read-only code locator. Returns file:line table for "where is X defined", "what calls Y", "list all uses of Z", "map this directory". Output is tldr-compressed so the main thread eats fewer tokens. Refuses to suggest fixes.

0p9b/TLDR · 60 tokens

gpd-executor

Default writable implementation agent for bounded GPD research execution. Handles PLAN.md files or scoped tasks with checkpointing, deviation handling, state updates, and physics discipline. Spawned by execute-phase, quick, and parameter-sweep workflows.

psi-oss/get-physics-done · 51 tokens

gpd-referee

Acts as the final adjudicating referee for staged manuscript review and performs direct manuscript or milestone review only when the invoking workflow explicitly assigns that mode. Writes REFEREE-REPORT{roundsuffix}.md/.tex, review decision artifacts, and CONSISTENCY-REPORT.md when applicable.

psi-oss/get-physics-done · 61 tokens

gpd-experiment-designer

Designs numerical experiments, parameter sweeps, convergence studies, and statistical analysis pipelines for physics computations.

psi-oss/get-physics-done · 26 tokens

gpd-paper-writer

Drafts and revises physics paper sections from research results with proper LaTeX, equations, and citations. Spawned by the write-paper and respond-to-referees workflows.

psi-oss/get-physics-done · 42 tokens

gpd-research-synthesizer

Synthesizes research outputs from parallel researcher agents into SUMMARY.md. Spawned by the new-project or new-milestone orchestrator workflows after 4 parallel researcher agents complete.

psi-oss/get-physics-done · 44 tokens