using-script-specialists

name	using-script-specialists
description	Use this skill for synchronous one-shot specialist invocations via `sp script` (CLI) or `sp serve` (HTTP daemon). These run READ_ONLY, template-driven specialists with `$var` substitution and return JSON in-process — no beads, no chains, no worktrees, no job lifecycle. Trigger when integrating a specialist into a service, script, or library, when the caller needs the output immediately, or when the work is a single LLM call with structured input/output. Do NOT use for tracked agent work — that belongs to `using-specialists`.
version	1.1.0
updated	2026-05-06T00:00:00.000Z
synced_at	a0e54d0c

Script-Class Specialists

sp script and sp serve are a separate runtime from the bead-first orchestration covered by using-specialists. They exist for service and library integration, not for agent chains.

Aspect	sp run (orchestration)	sp script / sp serve
Driver	bead contract	template + variables
Execution	supervised job, async	one-shot, synchronous
Permissions	READ_ONLY / MEDIUM / HIGH	READ_ONLY only
Worktrees	edit-capable provisions one	rejected
Output	result.txt + events.jsonl + bead notes	stdout JSON / HTTP body
Audit	.specialists/jobs/<id>/	one row in .specialists/db/observability.db

Use sp script from a shell or build pipeline. Use sp serve from a service that needs an HTTP endpoint backed by pi. The same .specialist.json runs under both.

When To Use This Skill

Trigger when:

• A service or script needs a single LLM-backed transform (summarize, classify, extract) returning JSON.
• You are integrating specialists into Python/Node code that cannot block on a supervised job lifecycle.
• The call is request/response shaped: variables in, structured output out.
• You need a sidecar HTTP endpoint (sp serve) to wrap a specialist for a service consumer that already speaks HTTP.

Do NOT trigger for: code review, debugging, implementation, multi-turn work, keep-alive sessions, anything that should write files. Those belong to using-specialists.

Specialist Compatibility (compatGuard)

A spec is rejected at request time (specialist_load_error) if any of:

• execution.interactive is true
• execution.requires_worktree is true
• execution.permission_required is anything other than READ_ONLY
• skills.scripts is non-empty (always rejected; no --allow-local-scripts bypass)
• prompt.task_template is missing
• a referenced $var in the chosen template is not supplied (template_variable_missing)

Author specs that explicitly target script-class:

{
  "specialist": {
    "metadata": { "name": "summarize-event", "version": "1.0.0", "category": "ingestion" },
    "execution": {
      "mode": "auto",
      "model": "anthropic/claude-haiku-4-5",
      "timeout_ms": 30000,
      "interactive": false,
      "response_format": "json",
      "output_type": "custom",
      "permission_required": "READ_ONLY",
      "requires_worktree": false,
      "max_retries" 
    
     
       
          
    
  

sp script — One-Shot CLI

sp script <specialist-name> \
  --vars key1=value1 --vars key2=value2 \
  [--template task_template] \
  [--model anthropic/claude-sonnet-4-6] \
  [--thinking medium] \
  [--timeout-ms 60000] \
  [--db-path /path/to/observability.db] \
  [--single-instance <lock-name>] \
  [--no-trace] \
  [--json]

Behaviour:

• Loads the spec via SpecialistLoader (same loader as sp run).
• Renders prompt.task_template (or named template) with --vars, then feeds the rendered prompt via stdin.
• --db-path /path/to/observability.db is an exact SQLite file path; omit it to use the project default .specialists/db/observability.db.
• Spawns pi in JSON mode with no session, no extensions, no tools, and offline; forwards the resolved model, optional --thinking, and --system-prompt when prompt.system is set (full override, not append).
• Returns the final assistant text on stdout. With --json, returns the full ScriptGenerateResult envelope.
• Writes one row to .specialists/db/observability.db (same writer as sp run).

Exit codes:

• 0 — success.
• non-zero — failure; with --json, body has success: false and error_type.

Use --single-instance <lock> when concurrent invocations of the same logical job must be serialized (cron, batch script).

sp serve — HTTP Daemon

sp serve \
  [--port 8000] \
  [--concurrency 4] \
  [--queue-timeout-ms 5000] \
  [--shutdown-grace-ms 30000] \
  [--project-dir /path/to/project] \
  [--fallback-model anthropic/claude-haiku-4-5]

POST /v1/generate:

{
  "specialist": "summarize-event",
  "variables": { "event_id": "abc", "body": "..." },
  "template": "task_template",
  "model_override": "anthropic/...",
  "timeout_ms": 60000,
  "trace": true
}

Response (200, success):

{
  "success": true,
  "output": "<final text>",
  "parsed_json": { "summary": "..." },
  "meta": {
    "specialist": "summarize-event",
    "model": "anthropic/claude-haiku-4-5",
    "duration_ms": 1234,
    "trace_id": "<uuid>"
  }
}

Response (200, failure):

{ "success": false, "error": "...", "error_type": "..." }

Error types: specialist_not_found | specialist_load_error | template_variable_missing | auth | quota | timeout | network | invalid_json | output_too_large | internal.

400 is reserved for malformed HTTP. 429 returns when concurrency cap is saturated past queue-timeout-ms.

Operational Rules

• One pi subprocess per in-flight request, bounded by --concurrency.
• Credentials come from pi's own ~/.pi/agent/auth.json. The service never touches API keys.
• Observability DB is shared with sp run. Audit trail is unified.
• The service is sidecar-per-consumer: no multi-tenant routing, no session state, no orchestration. If you need orchestration, use sp run + beads.
• For container deployments, see docs/specialists-service-install.md. Image runs as non-root UID 10001; bind-mount ~/.pi and .specialists/.

When To Switch Back To using-specialists

If any of these become true mid-design, drop script-class and use the orchestration runtime:

• The work needs to write files.
• The caller wants a multi-turn / keep-alive session.
• A reviewer pass is needed.
• The work should be tracked as a bead with auditability beyond a single observability row.
• The output is iterative (steer / resume).

What Not To Put Here

• Bead workflow, chains, epics, reviewers, worktrees — those live in using-specialists.
• Orchestration MCP tooling (use_specialist).
• Long-running multi-turn examples.

Reference

• docs/specialists-service.md — HTTP contract and operational notes.
• docs/specialists-service-install.md — Docker/Podman install path.
• docs/script-specialists.md — historical context for the script-class shape.
• src/cli/script.ts, src/cli/serve.ts, src/specialist/script-runner.ts — runtime.