Why the CLI is agent-friendly
- Structured JSON on every command. Pipe-detection auto-switches to JSON, or pass
--jsonexplicitly. Errors return a{ "error": { "message": "..." } }envelope on stderr. See Output format. - Stable exit codes.
0success,2usage,3authentication,4not found,5forbidden. Branch on the integer, not the prose. See Exit codes. - Idempotent reads. Every
list,get,export, and analysis call is a pure read. Running it twice produces the same result and never mutates state. - Predictable mutation surface.
update,create,delete,merge,attach, andimport createare the only write paths, each documented with required flags and explicit confirmation where destructive (--confirm). llms.txtdiscovery. Fetch the llms.txt index for a flat list of every docs page, suitable for embedding in an agent’s retrieval layer or context window.- Skills bundled with the binary. 11 skill files ship inside the GitHub repo. Install them all with
npx skills add https://github.com/talkvalue/cliand the agent can navigate the whole CLI surface without reading every doc page first.
How an agent uses the CLI
A typical agent loop looks like:AI agent skills
The 11 bundled
SKILL.md files (7 command-group wrappers, 1 shared reference, and 3 workflow recipes) installable via npx skills add.Recipes
Multi-step shell workflows your agent can compose: registrants, CSV import, channel analysis, jq scripting.
Related
- Authentication. How to use
TALKVALUE_TOKENfor headless agent runs. - Global flags.
--json,--profile,--api-url, and the rest. - Troubleshooting. Common failure modes by exit code.
- llms.txt. Flat index of every docs page.
