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Persona-Grata

Persona-Grata is a scaffolding utility that binds AI personas to harnesses to produce an embodied, functional agent. It helps users connect professional LLM orchestration harnesses (e.g., Claude Code, the Codex CLI, and Goose) with customized endpoints.

Install

Install via pipx, uv, or your other favorite package management tool:

pipx install persona-grata

Run

Run it directly:

persona-grata <persona> [harness]*

Examples

To install a persona for the official kimi servers and use it with Claude Code:

persona-grata kimi claude

If you have custom endpoints or other settings, create and run with an agent file:

persona-grata custom_agents.yap

Read more about configurations in the Custom Agents Guide.


Overview: Agents, Personas, & Harnesses

We combine a persona (representing the mind and experience) with a harness (the mechanism used to impact the world) to yield an agent.

...but what does that actually mean?

An agent is an entity that can act on the world around it - it has a model of its universe, an inference-based (data-derived) decision-making process, a set of actions, and some knowledge of the results of its actions (see also The Craik Model of Intelligence.) An agent requires not just the ability to think, but also the ability to act.

A persona is that thinking part of an agent - i.e., its 'mind' (endpoint, model, & parameters) and 'experiences' (system prompt, context, etc.)

To interact with the world, we can use a harness (sometimes called an orchestrator) to provide toolsets and communication mechanisms; these include Claude Code, Codex CLI, Goose, & many others.

By combining a persona with a harness, we get the fully embodied agent.


Usage

The utility reads agent definitions from provided Yapyon (.yap) files (which describes how personas connect to harnesses) and configures your local environment. The sample agents-example.yap file can serve as a starting point; the bundled harness profiles are 'ready' to go and do not require modification.

Known Endpoints & Harnesses

Persona-Grata comes with "out of the box" support for the following endpoints and harnesses; for each endpoint, a default persona is derived:

Endpoint for Service Persona
api.moonshot.ai:443 kimi
localhost:13305 lemonade
localhost:9931 llamacpp
localhost:1234 lmstudio
localhost:8000 local_8000
localhost:8080 local_8080
localhost:11434 ollama
api.minimax.io:443 minimax
api.ai.it.ufl.edu:443 navigator
Application/Tool Harness
Claude Code claude
OpenAI Codex CLI codex
Goose AI Agent goose

Setup an Agent

To setup an agent from a persona and harness, run persona-grata <persona> [harness]*:

persona-grata kimi

Sets up kimi for all known harnesses

persona-grata minimax claude codex

Sets up minimax for use with Claude Code and Codex CLI

If you need a more customized solution, an agent definition file provides additional flexibility:

agents.yap

personas:
  orion:
    persona_desc: "Orion Toolkit"
    mind:
      endpoint: "https://api.cybertron.space"
      model: "alpha-3-on"

Then, run:

persona-grata agents.yap orion claude

Setup the custom persona (Orion Toolkit) with Claude Code.

Or, to install all agents and harnesses, run without persona and/or harness names:

persona-grata agents.yap

Setup every persona in the file with all known harnesses.

pg is a shorter alias for the same command: pg kimi claude.

Designations & Names

An agent's designation is <persona>+<harness>. It names one agent, so it settles the harness on its own:

pg kimi+claude

The same as pg kimi claude.

A name is yours to choose, and is how the agent is invoked. Pass --name to set one:

pg --name scout local_ollama+codex

Sets up the agent and installs it as scout rather than local_ollama_codex.

A name replaces that command rather than adding a second one, so an agent always has exactly one way to run it; naming it again renames it. Use the name wherever a designation goes — pg -r scout removes it, and releases the name. An agent you never name keeps its designation as its name.

Create a Configuration via CLI

For one-off variants or local model servers, persona configurations can be defined by arguments:

pg --endpoint http://localhost:8675 --model llama3 --no-token ollama claude

Sets up a local Ollama model as the persona "ollama", for Claude Code.

The CLI can also be used to update an existing persona:

pg --update --model kimi-k2-0905-preview kimi codex

Sets kimi up with Codex CLI, using a different model just this once.

By default, a definition is ephemeral, but the configuration can be exported if desired:

pg --endpoint http://who.dr:99 --model llama3 --no-token --export "clauma.yap" ollama claude

Exports the configuration to clauma.yap.

Export, update, and new persona creation are mutually exclusive:

Flag New OK? Existing OK? Writes? Reads New? Reads Existing?
--export Yes Yes No Yes Yes
--update No Yes Yes Yes Yes
--create Yes No Yes Yes Yes

The API key/token can be read, verified, then stored directly, replacing any existing key/token:

pg --token ~/keys/moonshot.key kimi claude

Sets kimi up with Claude Code, taking the key from ~/keys/moonshot.key.

The same settings can also be asked for rather than typed:

pg -i

Asks for a name, description, endpoint, model, key, and harnesses, then offers to save the result. Asks for a name, description, endpoint, model, key, and harnesses, then offers to save the result. Interactive mode supplies whatever flags did not, combining one of the actions above; e.g., pg -i --update kimi only asks for missing elements. It cannot be paired with --remove.

Remove an Agent

Pass --remove (or -r) to remove the harness-persona wrapper & harness config directory:

pg --remove kimi codex

Removes the Codex CLI agent for kimi, leaving Claude Code and the stored token alone.

pg --remove kimi

Removes every kimi harness, then asks whether to delete the stored API token, if there is one.

Interaction

The script automatically adds a shell wrapper to your .bashrc, .zshrc, or .profile, depending on your shell. After running setup and sourcing your config (source ~/.bashrc) or opening a new terminal, you can launch the agent:

<persona>_<harness> [arguments]

A $SHELL persona-grata doesn't recognise is reported, not assumed; the wrapper is written in plain POSIX shell syntax, so any POSIX shell will run it.

Names — of personas, harnesses, dialects, and agents — are 1–64 ASCII letters, digits, and _, and do not start with a digit: the same rule kanibako uses, so every name is a valid shell function name.

Parameters Summary

Parameter Sets
--endpoint URL Set mind.endpoint to URL
--model NAME Set mind.model to NAME
--desc TEXT Set persona_desc to TEXT
--no-token token — no key prompt or verification*^
--create Stores a new persona; fails if name is taken
--update Replace an existing persona, if it exists
--export FILE Export a template for this configuration to file named FILE
-i, --interactive Ask for whatever is not given above; offers to save the result
--token FILE Read the API key from FILE rather than prompting for it^
--name NAME Call this agent NAME, and install it as the command NAME
--remove, -r Remove the named agent(s); offers to delete the token

*If the --no-token flag is not included, connections to keyless-only servers will fail.

^--token and --no-token are mutually exclusive.

Agent Configuration & Templates

Definitions are managed in an agents file written in yapyon, a YAML-like format. It describes one or more personas and/or harnesses. Unlike YAML, yapyon has no unquoted strings — write model: "kimi-k3", not model: kimi-k3 — and keys are bare identifiers.

Values can be computed from other values with y-strings: y"{<reference>}" is replaced by the value the reference names, and text around it is kept (y"{path}/token").

  • Context Lookup: A reference is looked up from where it is written outward, so a value nearby wins (e.g., {api_uri}, {path}).
  • Hierarchical References: Absolute references to any value in the configuration via dot-notation (e.g., {personas.orion.mind.model}).
  • Reserved Identifiers: {__PARENT__} resolves to the immediate parent node in the configuration tree and {__KEY__} to a node's own key, so {__PARENT__.__KEY__} in a persona definition yields that persona's ID.
  • Serializers: a reference ending in __AS_JSON__(), __AS_TOML__(), __AS_YAML__(), or __AS_YAPYON__() renders a subtree as a harness file (content: y"{config_store.__AS_JSON__()}"). All four drop unset entries — "", None, empty maps — so the harness never sees a key the persona left empty. __AS_YAPYON__ is the one that also carries multimaps and bytes.
  • Subscripts: any segment may be indexed by another reference (e.g., {providers[chosen].url} is "the entry of providers named by chosen"). Lists index by position — [1], [-1] included.
  • Functions: match_first(key_set, items) yields the first member of key_set found among items' keys, reading the list as a preference order; it is how a harness and a persona settle on a dialect (y"{match_first(supported_dialects, mind.dialects)}").

A y-string always produces text, so it can splice in a string, number, or None, but not a whole list or map. A list may hold y-strings as its items (supported_dialects: [y"{preferred}"]). Write {{ or }} for a literal brace.

Environment variables are read with {$NAME} — y"{$HOME}/agents" — and an unset one is an error rather than an empty string; {__ENV__("NAME", "fallback")} supplies a default instead. Only variables the store allows can be read (by default the standard ones such as HOME and PATH; see env_allow / env_add in the Config Reference Manual). A plain string is never expanded: "$HOME/agents" stays exactly that text.

For more about templates & configuration, see the Config Reference Manual.

Security

To prevent secret leakage:

  • API tokens are stored in files with 0600 permissions.
  • The utility handles tokens by path, avoiding printing secrets to logs or transcripts.
  • A .secret_path file is created in the persona's home directory containing the path to the token for discovery by other tools.

License & Contributing

Persona-Grata is released under the GNU General Public License v3.0 or later; see LICENSE.md.

Contributions generated in whole or in part with AI tools are welcome, subject to the project's AI policy.

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