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.
npx skills add withoneai/one-agent-plugin --skill docusealgit clone --depth 1 https://github.com/withoneai/one-agent-pluginWrote 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/skills/withoneai/one-agent-plugin/docuseal)<a href="https://agentmods.dev/skills/withoneai/one-agent-plugin/docuseal"><img src="https://agentmods.dev/badge/skills/withoneai/one-agent-plugin/docuseal/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/skills/withoneai/one-agent-plugin/docuseal"><img src="https://agentmods.dev/badge/skills/withoneai/one-agent-plugin/docuseal.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 | $0.00114 | $0.01790 |
| Opus 5 | $0.00057 | $0.00895 |
| Sonnet 5 | $0.00023 | $0.00358 |
| Haiku 4.5 | $0.00011 | $0.00179 |
Grade A, and why
docuseal 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.
This is a copy
77% identical to 2-chat — 268 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.
How it starts
The opening of the file, as written. The whole thing — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Docuseal through One
DocuSeal is an open-source eSignature and document workflow platform that enables users and developers to send, sign, and manage legally binding documents with customizable templates, API integrations, and self-hosting options for greater control, security, and automation.
One exposes Docuseal 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
- Find the action in the table below, or call
search_one_platform_actionswith platformdocusealif it is not listed. - Call
get_one_action_knowledgewith the action id. Do this every time, including for actions in this table. The table gives you the id, not the parameters. - Call
execute_one_actionwith 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 Docuseal 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 Docuseal 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
Templates
| Action | Method | Path | Action id |
|---|---|---|---|
| Get a Template | GET | /templates/{{id}} |
conn_mod_def::GKzwkZ9kDhA::0fnIvTkuSjeSKFnO9m1jUg |
| List Templates | GET | /templates |
conn_mod_def::GKzwkbsVPhg::r9_VST6pRPeDsBcev8q-kA |
| Archive a Template | DELETE | /templates/{{id}} |
conn_mod_def::GKzwkP4mzYA::WTpuyj6FTMWcxSSzXCLAkw |
| Clone a Template | POST | /templates/{{id}}/clone |
conn_mod_def::GKzwkPrzvdA::HPJgeO1xRPyiqE_QVw6R-Q |
| Create a Template from HTML | POST | /templates/html |
conn_mod_def::GKzwkQQzihA::zPBqM7dfQraFTe9xLP9uTA |
| Create a Template From PDF | POST | /templates/pdf |
conn_mod_def::GKzwkao97sg::W51j7WOdQPSXgOinKSWo7w |
| Create a Template From Word DOCX | POST | /templates/docx |
conn_mod_def::GKzwkajpV2A::9fDYe5hhQiWRT2wwatXmQA |
| Merge Templates | POST | /templates/merge |
conn_mod_def::GKzwkcldO7A::DR8HBMUkQre20g5Aywr9sA |
| Update a Template | PUT | /templates/{{id}} |
conn_mod_def::GKzwkl6lPJA::2qFWhziTSxWJ3jRgPa2PGw |
| Update a Template's Documents | PUT | /templates/{{id}}/documents |
conn_mod_def::GKzwkle726A::1shfyXRlRjWZtsc0DcFjdA |
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.
- 5d ago First seen · 87 lines · 0 tokens per session scan A 8403595d7afb
docuseal is a skill published in the GitHub repository withoneai/one-agent-plugin (1 stars, last pushed 19d ago), licensed MIT. It adds 114 tokens to every session and 1,790 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. It is 77% identical to 2-chat, differing in 268 lines, and is treated as a copy.
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