| name | yolop-config |
| description | View and change yolop's own configuration — default provider and model, per-provider API tokens and models, endpoint base URLs, attribution, and harness capabilities. Use when the user asks to configure yolop, set a default provider/model, store an API key, point at a custom endpoint, enable/disable capabilities, or asks "what is your config / what can you configure". |
| user-invocable | true |
Yolop configuration
yolop stores its settings in a single TOML file (settings.toml in the yolop
config dir). The file is loaded tolerantly — unknown keys are ignored, never
fatal — and every known key carries semantics (title, description, type,
default, examples) that you can read at runtime. This skill is the entry point
for inspecting and editing that configuration the way a user describes it.
Do not hand-edit the TOML with the file tools. Use the schema-aware tools so
values are validated and persisted atomically.
Inspect
- Call
get_config with no arguments to list every configuration key with
its meaning, type, default, examples, and current value. Secrets (API
tokens) are shown only as stored / unset, never echoed.
- Call
get_config with a single key (e.g. default_provider,
models.anthropic, tokens.openai) to focus on one entry.
- For harness capabilities, use
get_config key=capabilities (registered catalog,
stored overrides, effective harness) or get_config key=capabilities.<ref>
(per-capability schema metadata from config_schema / config_ui_schema).
Lead with get_config whenever you are unsure of the exact key name or the
accepted values — the returned schema is the source of truth, so you never have
to guess.
Change
Call set_config with a key and a value for scalar settings:
set_config key=default_provider value=anthropic — the default provider when
neither --provider nor an env credential forces a choice.
set_config key=default_model value="claude-sonnet-4-5" — global fallback
model for the active provider. A per-provider pick wins over it.
set_config key=models.openai value="gpt-5.5 high" — remember a model for one
provider (survives provider switches). The spec is model [reasoning-effort].
set_config key=tokens.anthropic value=… — store an API token (owner-only on
disk). Environment variables still override stored tokens.
set_config key=base_urls.custom value=http://localhost:8000/v1 — endpoint
for the OpenAI-compatible custom provider.
set_config key=attribution value=off — turn commit/PR attribution on/off.
Pass value=clear to unset an optional or secret key
(e.g. set_config key=tokens.openai value=clear).
Harness capabilities
Overrides are an ordered [[capabilities]] list in the same file. Append
entries with set_config key=capabilities and a json object (validated via each
capability's validate_config). Pass value=clear to drop all stored overrides.
[[capabilities]]
ref = "message_metadata"
fields = ["timestamp"]
[[capabilities]]
ref = "duckduckgo"
enabled = false
Tool equivalents:
set_config key=capabilities json={"ref":"message_metadata","fields":["timestamp"]}
set_config key=capabilities json={"ref":"duckduckgo","enabled":false}
set_config key=capabilities json={"ref":"web_fetch","enable_file_download":false}
set_config key=capabilities json={"ref":"some_cap","append":true,...} — duplicate instance
set_config key=capabilities value=clear — remove all stored overrides
Provider and model edits are persisted and take effect on the next run. To
switch the live model in the current session, use the interactive /setup
command instead.
Related surfaces
- Durable preferences / memory ("remember that I prefer terse answers"):
these are not config keys. Use the
remember / recall / forget tools
(the global memory capability), not set_config. Memory tuning
(disclosed_titles, recall_limit, soft_cap) is per-capability config
exposed via the capability's config_schema, not a settings.toml key.
- Behavioral hooks (block/allow/audit tool calls): use the
yolop-hooks
skill and the hooks capability tools.
- Interactive provider/model setup: the
/setup command runs a guided
wizard and switches the live model immediately.