agents-comparison

agents-comparison is an agent for coding agents from Smart-AI-Memory/attune-ai. It costs 3 tokens per session (295 once invoked), scanned A, original, Apache-2.0.

A comparison guide for three Attune features: custom AI agents, packaged workflows, and interactive wizards. It explains when each entry point is appropriate.

In plain words
What is it for?
Use it to compare framework support, entry points, and use cases before implementing an agent task.
Why use it?
It helps you choose between building your own agent, using a prepared pipeline, or following a guided process.

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/smart-ai-memory/attune-ai/comparison
Clone the repo
git clone --depth 1 https://github.com/Smart-AI-Memory/attune-ai

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 agents-comparison

README.md
[![agentmods](https://agentmods.dev/badge/agents/smart-ai-memory/attune-ai/comparison.svg)](https://agentmods.dev/agents/smart-ai-memory/attune-ai/comparison)
Your own site
<a href="https://agentmods.dev/agents/smart-ai-memory/attune-ai/comparison"><img src="https://agentmods.dev/badge/agents/smart-ai-memory/attune-ai/comparison.svg" alt="Measured on agentmods" height="20"></a>
Per session 3 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 295 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 $0.00003 $0.00295
Opus 5 $0.00002 $0.00148
Sonnet 5 $0.00001 $0.00059
Haiku 4.5 $0.00000 $0.00030

Measured 3d ago against content hash 7ae62f2fc49f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

agents-comparison 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 3d 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.

.help/templates/agents/comparison.md · 28 lines

What it actually says

Universal Agent Factory — create, run, and orchestrate AI agents across frameworks

Comparison

The Agent Factory is the build-your-own-agent surface, distinct from the packaged workflows and from wizards:

agents (Factory) workflows wizards
What Create/run/orchestrate custom agents across frameworks Pre-built analysis pipelines (security, review, …) Interactive multi-step guided flows
Entry AgentFactory(...) + await invoke/run attune workflow run <slug> /wizard skill + await run()
Frameworks native / langchain / langgraph / autogen / haystack n/a n/a

Reach for the Factory when you need bespoke agents or want framework portability; reach for workflows when a packaged pipeline already does the job; reach for wizards for an interactive, user-in-the-loop task.

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. 3d ago First seen · 28 lines · 3 tokens per session scan A 7ae62f2fc49f

Subscribe to this mod's changes

agents-comparison is an agent published in the GitHub repository Smart-AI-Memory/attune-ai (10 stars, last pushed today), licensed Apache-2.0. It adds 3 tokens to every session and 295 once invoked, about $0.0000 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 2026-08-31.

Related

Other agents, from other repositories

plan-guardian

Drift check for the active cc-memory plan. Read .ccm/PLAN.md + .ccm/PROGRESS.md, compare against recent activity, and report whether the live work is still aligned with the plan. Read-only — do not edit files or write to the DB.

skymanbp/cc-memory · 61 tokens

surveyor

Read-only breadth sweeps over a codebase - enumerate, list, trace a chain end to end ("list every stage in order", "which files import X", "where does this pipeline end"). Returns the list or the ordering, never file dumps. Use scout instead when the answer needs judgement about what code does. Never modifies anything.

AqueGen/model-routing · 71 tokens

scout

Read-only codebase explorer. Use for "where is X", "how does Y work", "which files touch Z" - returns conclusions with file:line refs, never file dumps. Never modifies anything.

AqueGen/model-routing · 45 tokens

verifier

Cheap gate before accepting another agent's diff - does it match the task (scope, completeness, obvious breakage)? Returns PASS/FAIL with reasons. NOT a code review - it catches "did the wrong thing"; real reviews go to reviewer.

AqueGen/model-routing · 52 tokens

test-runner

Runs tests, builds, and linters; reports compactly. Mechanical run-and-report only. Do NOT use when failures need interpretation or fixing - that is e2e-runner or the main session.

AqueGen/model-routing · 45 tokens

_SCHEMA

Real subagent persona definitions. Each .json defines one agent — its system prompt, tool grants, skill wrappers, trigger signals, success metrics, and per-agent learnings file.

itsribbZ/Godspeed · 0 tokens