affinda

affinda is a skill for Claude Code, Codex from withoneai/one-agent-plugin. It costs 0 tokens per session (5,559 once invoked), scanned A, a copy of 2-chat, MIT.

A document-processing platform that extracts, transforms, matches, and validates information from complex documents.

In plain words
What is it for?
Use it to work with Affinda through connected tools: check the integration, read the exact action instructions, then run document-processing operations with the required fields.
Why use it?
It helps automate document-heavy workflows and send information grounded in source documents into business systems such as Dynamics 365, Salesforce, and Xero.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

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/withoneai/one-agent-plugin/affinda
Any agent
npx skills add withoneai/one-agent-plugin --skill affinda
Clone the repo
git clone --depth 1 https://github.com/withoneai/one-agent-plugin

Made for: Claude Code, Codex.

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 affinda

README.md
[![agentmods](https://agentmods.dev/badge/skills/withoneai/one-agent-plugin/affinda.svg)](https://agentmods.dev/skills/withoneai/one-agent-plugin/affinda)
Your own site
<a href="https://agentmods.dev/skills/withoneai/one-agent-plugin/affinda"><img src="https://agentmods.dev/badge/skills/withoneai/one-agent-plugin/affinda.svg" alt="Measured on agentmods" height="20"></a>
Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,559 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 75% copy Near-identical to another mod 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 $0.00000 $0.05559
Opus 5 $0.00000 $0.02780
Sonnet 5 $0.00000 $0.01112
Haiku 4.5 $0.00000 $0.00556

Measured 5d ago against content hash 6e6a91cd3fa2, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

affinda 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 5d 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.

Origin

This is a copy

75% identical to 2-chat — 300 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

platforms/one-affinda/skills/affinda/SKILL.md · 219 lines

How it starts

The opening of the file, as written. The whole thing — 219 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Affinda through One

Affinda is an intelligent document processing platform that uses AI to extract, transform, match, and validate data from complex documents, enabling businesses to automate high-stakes document workflows and send source-grounded information into systems such as Dynamics 365, Salesforce, and Xero.

One exposes Affinda through four MCP tools. The table below carries real action ids from One's knowledge base, so for a common operation you can skip search and go straight to reading the action's parameters.

How to run an action

  1. Find the action in the table below, or call search_one_platform_actions with platform affinda if it is not listed.
  2. Call get_one_action_knowledge with the action id. Do this every time, including for actions in this table. The table gives you the id, not the parameters.
  3. Call execute_one_action with parameters copied from that knowledge.

Never guess a parameter name, a body field, or an enum value. The knowledge has the real schema, and a guessed field is either a 400 or a silent write of the wrong thing.

Before you start

Call list_one_integrations once and confirm Affinda is connected. If it is missing, the user has not connected it: say so and point them at https://app.withone.ai rather than reaching for raw HTTP.

Each connection carries an access field. If it reports {"policy": "methods", "methods": ["GET"]} the agent is read-only here, so plan a read-only answer instead of attempting a write that will be refused.

Before a write

Creates, updates, deletes and sends land on a real Affinda account and cannot be recalled. State the action and the specific target in one line before the first write in a task, and let the user stop you. Reads need no confirmation.

Actions

Documents

Action Method Path Action id
Get a Document's Redacted Version GET /v3/documents/{{identifier}}/redacted conn_mod_def::GMiFnb1jn0A::wvTpg9B2TPeIQbjBufbsRg
Get a Specific Document GET /v3/documents/{{identifier}} conn_mod_def::GMiFnbqlrAg::vSB8SZkmS3qgFiYVs94rxw
List Documents GET /v3/documents conn_mod_def::GMiFnUtlxJA::Nb6xs5wUTPmpOUNSUrdjPQ
List Documents for an Index GET /v3/index/{{name}}/documents conn_mod_def::GMiFn15Yb7A::ztJhGT4RTsei9DKcPMpkiQ
Add Tag to Documents POST /v3/documents/batch_add_tag conn_mod_def::GMiFobradvA::sD_9KjgrR5qkGyPJDAB7mw
Batch Remove Tag from Documents POST /v3/documents/batch_remove_tag conn_mod_def::GMiFolf6kgg::pLrZJnduTV6OBw7eTTR1VQ
Create From Data Using Documents POST /v3/documents/create_from_data conn_mod_def::GMiFnsul8ng::u29MGuBfT5eDjFISSPhE5g
Delete a Document DELETE /v3/documents/{{identifier}} conn_mod_def::GMiFnSUJNhA::ZJL4cpAyQeGmEaWz-0oBtA
Index a New Document for an Index POST /v3/index/{{name}}/documents conn_mod_def::GMiFoHyo5jg::C5QcqrDtQrGY3meaLntHLg
Re-index a Document in an Index POST /v3/index/{{name}}/documents/{{identifier}}/re_index conn_mod_def::GMiFoUhoUrg::_88cQ7rXT2S5XuGFCD6tlg
Update a Document PATCH /v3/documents/{{identifier}} conn_mod_def::GMiFncFFMrg::sLsp5UIFQXWkmxyoilQNjw
Update Data for a Document POST /v3/documents/{{identifier}}/update_data conn_mod_def::GMiFoUR8lbA::YEOCSwEsRUeKkiJNs_4DMw

Read the full file on GitHub · 219 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. 5d ago First seen · 219 lines · 0 tokens per session scan A 6e6a91cd3fa2

Subscribe to this mod's changes

affinda is a skill published in the GitHub repository withoneai/one-agent-plugin (1 stars, last pushed 16d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 5,559 tokens. A static security scan graded it A with 0 findings. It is 75% identical to 2-chat, differing in 300 lines, and is treated as a copy.

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