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Multica Creating Agents

  • 17 installs
  • 44k repo stars
  • Updated August 5, 2026
  • multica-ai/multica

Helps with ai & agent building tasks during AI-assisted development.

About

multica-creating-agents is a Claude Code skill for ai & agent building. It helps solo builders move faster with AI-assisted coding.

  • multica-creating-agents
  • AI & Agent Building
  • AI-coding skill

Multica Creating Agents by the numbers

  • 17 all-time installs (skills.sh)
  • +7 installs in the week ending Aug 4, 2026 (Skillselion tracking)
  • Ranked #10,861 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/multica-ai/multica --skill multica-creating-agents

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Listed on Skillselion
Installs17
repo stars44k
Last updatedAugust 5, 2026
Repositorymultica-ai/multica

What it does

Helps with ai & agent building tasks during AI-assisted development.

Files

SKILL.mdMarkdownGitHub ↗

Creating Multica agents

This is the contract for Multica's agent-creation path: what the create entry points accept, what the server validates and rejects, how each field is persisted, and which fields the daemon actually reads at claim time. It is not a parameter manual — it states source-traced facts, and every claim is backed by file:line in references/creating-agents-source-map.md.

Quick start (read-only inspection)

These commands read state and have no side effects:

multica agent get <agent-id> --output json      # full persisted agent record
multica agent skills list <agent-id> --output json   # current skill bindings
multica agent env get <agent-id> --output json  # plaintext env (owner/admin only, agents denied)

agent get returns the persisted agent including runtime_id, model, thinking_level, custom_args, has_custom_env, custom_env_key_count, and skills. It never returns plaintext custom_env.

Core model

An agent is a workspace-scoped row (table agent). Creation is a single POST /api/agents (multica agent create). At task claim time the daemon re-reads the agent row and assembles the runtime payload — so the persisted fields, not the create-time output, are what the agent runs on.

Two distinct text fields, often confused:

  • description is a catalog summary. It is stored and shown in listings; the

daemon does NOT inject it into the agent's runtime prompt. Treat it as human-facing metadata only. Capped at 255 Unicode code points.

  • instructions is the runtime behavior contract. The daemon reads it at

claim time and ships it to the provider as the agent's durable instructions. Persona, responsibilities, boundaries, output and escalation rules go here, not in description.

CLI / API entry points

Minimum create call (--name and --runtime-id are both required):

multica agent create --name <name> --runtime-id <runtime-id> \
  --description "<short catalog summary>" \
  --instructions "<runtime behavior contract>" \
  --output json

runAgentCreate builds a JSON body and posts it to /api/agents. It only adds a key when its flag was provided — description/instructions on a non-empty value, the rest (runtime-config, custom-args, model, thinking-level, visibility, …) on the flag being Changed — so omitted flags fall through to server defaults rather than sending empty strings.

The HTTP body (CreateAgentRequest) accepts: name, description, instructions, runtime_id, runtime_config, custom_env, custom_args, model, thinking_level, visibility, max_concurrent_tasks, mcp_config.

Field contracts

FieldPersisted asValidated?Consumed by
nameagent.namerequired, 400 if emptylistings, runtime payload
descriptionagent.description400 if > 255 code pointscatalog/listing only — NOT the runtime prompt
instructionsagent.instructionsnonedaemon → provider at claim time
runtime_idagent.runtime_idrequired (400) + must resolve to a runtime in this workspaceselects runtime/provider
modelagent.model (nullable)none beyond runtime supportdaemon reads; empty = runtime default
thinking_levelagent.thinking_level (nullable)provider-level enum; unknown literal → 400daemon; empty = runtime default
custom_argsagent.custom_args (JSON array)JSON shape checked CLI-side; server stores as-isdaemon (extra CLI switches); defaults to []
runtime_configagent.runtime_config (JSON)JSON shape checked CLI-side; server stores as-isruntime-specific config; defaults to {}
custom_envagent.custom_env (JSON object)daemon (process env); see Env & secrets
mcp_configagent.mcp_config (raw JSON)CLI checks it is a JSON object or null; server stores as-is. At create, literal null is dropped (no-op); at update, null clears the columndaemon → provider (MCP servers) — runtime-consumed; redacted on read
visibilityagent.visibilityaccess control; defaults to private; gates who can read/route a private agent (e.g. a private squad leader) — NOT the runtime prompt
max_concurrent_tasksagent.max_concurrent_tasksscheduler task cap; defaults to 6

Defaults when omitted: runtime_config{}, custom_env{}, custom_args[], visibilityprivate, max_concurrent_tasks6 (all materialized server-side before the insert). custom_args/runtime_config are typed []string/any and marshaled as-is — the JSON-shape rejection happens in the CLI, not the create handler.

thinking_level is validated only at the provider level: an unrecognized literal returns 400, but a value that is valid for the provider yet unsupported for the chosen model is NOT rejected here — that gap surfaces as a daemon-side task error at execution time.

Set it from the CLI with --thinking-level on agent create and agent update, mirroring --model: the flag is a thin pass-through to the top-level thinking_level field, and on update an empty string (--thinking-level "") clears it back to the runtime default. The CLI deliberately does not enumerate the valid levels — they are runtime/model-specific (Claude low|medium|high|xhigh|max, Codex none|minimal|low|medium|high|xhigh, and others), so it forwards whatever you pass and lets the server's provider catalog accept or reject it. A runtime whose provider has no thinking concept rejects any non-empty value with a 400.

model vs custom_args

model is a first-class persisted column the daemon reads directly. custom_args are raw provider CLI args. The CLI help notes that some providers (codex app-server, openclaw) reject --model inside custom_args — but that is documented CLI guidance, not a server-enforced invariant; nothing in the create handler inspects custom_args for a model flag.

Env & secrets

custom_env is secret material. The CLI offers three input channels; two keep secrets out of shell history and the process list:

multica agent create --name <name> --runtime-id <runtime-id> --custom-env-stdin --output json
multica agent create --name <name> --runtime-id <runtime-id> --custom-env-file <0600-json> --output json

--custom-env-stdin reads the JSON object from stdin; --custom-env-file reads it from a file (suggested mode 0600). The third channel, --custom-env <json>, puts the value on the command line where shell history and ps can see it — avoid it for real secrets.

Read-side facts (these are the wrong assumptions to avoid):

  • Agent resources never expose plaintext custom_env. `agent

list/get/create/update and WS events return only has_custom_env (bool) and custom_env_key_count` (int).

  • Reading plaintext values requires the dedicated GET /api/agents/{id}/env

endpoint (multica agent env get). It is gated to workspace owner/admin members, and agent actors are denied regardless of the backing member's role — a running agent cannot read another agent's secrets.

  • Writing values after creation does NOT go through agent update. The generic

update handler rejects any custom_env field with a 400 ("use PUT /api/agents/{id}/env"). Plaintext env writes are handled by PUT /api/agents/{id}/env (multica agent env set), which is owner/admin-only and writes an audit row.

mcp_config

mcp_config is the agent's MCP server configuration (a JSON object such as {"mcpServers": {…}}). It is also secret material — MCP entries routinely embed API tokens — and offers the same three input channels as custom_env, on BOTH agent create and agent update:

multica agent create --name <name> --runtime-id <runtime-id> --mcp-config-file <0600-json> --output json
multica agent update <agent-id> --mcp-config-stdin --output json
multica agent update <agent-id> --mcp-config 'null'   # clears the config

--mcp-config-stdin / --mcp-config-file keep the value out of shell history and ps; the inline --mcp-config <json> does not. The CLI requires a JSON object or the literal null; a top-level array or primitive is rejected client-side, and empty stdin/file input errors rather than silently clearing.

Two ways mcp_config differs from custom_env:

  • It IS settable through `agent update`. Unlike custom_env, mcp_config

has no dedicated audited endpoint — the generic PUT /api/agents/{id} accepts it. Tri-state per the raw request body: field omitted → no change; null → clear; object → replace.

  • It is serialized on read, but redacted. agent get/list return

mcp_config only to callers allowed to view agent secrets; otherwise the field is null and mcp_config_redacted is true. Agent actors never see it, and a workspace may force redaction for everyone.

Skill binding

Creating an agent does NOT bind any workspace skill — binding is a separate call after the agent exists. Two distinct verbs:

  • add is additive — it merges the given ids with existing bindings

(POST /api/agents/{id}/skills/add).

  • set is replace-all — it overwrites the entire binding list with exactly

the given ids (PUT /api/agents/{id}/skills); --skill-ids '' clears all.

multica agent skills add <agent-id> --skill-ids <skill-id> --output json
multica agent skills list <agent-id> --output json

At claim time the daemon assembles the agent's skills as workspace-bound skills FIRST, then appends the platform built-in skills. LoadAgentSkills loads each bound skill's content plus its supporting files; built-in skills are embedded at compile time and loaded from SKILL.md + sibling files. Both reach the provider as skill content — which is why capability belongs in a bound skill, not pasted into instructions.

Side effects needing approval

Read-only (safe): agent get, agent skills list, agent env get.

State-changing (require an explicit instruction — do not run speculatively):

  • multica agent create — inserts a new agent row.
  • multica agent skills add / set — mutate bindings (set is destructive:

it drops bindings not in the new list).

  • multica agent env set — overwrites the full custom_env map and writes an

audit row.

Common wrong assumptions

  • "description is the prompt." It is not — only instructions reaches the

runtime. A rich description with empty instructions yields a named shell with no operating contract.

  • "Create binds the agent's skills." It does not; bind explicitly afterward.
  • "agent update can rotate env." It cannot — it 400s on custom_env; use the

env endpoint.

  • "mcp_config behaves like custom_env on update." It does not — mcp_config

IS settable via agent update (--mcp-config), with --mcp-config null to clear; only custom_env is gated behind the dedicated env endpoint.

  • "agent get shows env values." It shows only has_custom_env and

custom_env_key_count.

  • "An invalid thinking_level/model combo is caught at create." Only an

unknown provider-level literal is — model-specific gaps fail at run time.

  • "set and add are interchangeable for skills." set replaces all

bindings; using it when you meant add silently removes capabilities.

References

references/creating-agents-source-map.md maps every contract above to its file:line on the current tree, the runtime effect, and a safe read-only verification command.

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