# `Cyclium.Strategy.Template.AgenticTask`
[🔗](https://github.com/Cyclium/cyclium_ex/blob/main/lib/cyclium/strategy/template/agentic_task.ex#L1)

Strategy template for an **autonomous, tool-calling episode** — the same
interpret → validate → execute → summarize loop as
`Cyclium.Strategy.Template.Interactive`, but with no human in the loop.

Instead of a conversation turn, the run is seeded from an **objective** and the
triggering payload; the LLM then plans, calls tools as it sees fit (bounded by
`allowed_tool_signatures`), and terminates by calling the reserved
`finish_agentic_task` tool with its conclusion. The episode converges to
findings and/or outputs.

    context_assembly → interpret → validate → [preview] → execute → summarize
                                      ↑__________________________________|
                             (loop until the model calls finish_agentic_task)

## Objective (static + payload)

The objective is a template string, interpolated against the trigger payload
with `{{key}}` / `{{a.b}}` placeholders:

    strategy_config: %{
      objective: "Review resource {{resource_id}} for over-allocation and raise a finding if it is over limit.",
      role: "You are an operations analyst.",
      guidelines: ["Use read tools to gather evidence before concluding."],
      allowed_tool_signatures: [ ... ]
    }

A trigger payload may also carry its own `"objective"` string, which takes
precedence over the static template (still interpolated against the payload).

## Termination

The reserved `finish_agentic_task` tool is auto-injected into the tool menu
(the app does not declare it). Calling it ends the run; its args become the
converge result:

    {"tool": "finish_agentic_task", "action": "finish_agentic_task", "args": {
      "summary": "...",
      "confidence": 0.9,
      "findings": [{"action": "raise", "class": "over_limit", "summary": "...", ...}],
      "outputs":  [{"type": "slack", "dedupe_key": "...", "payload": {...}}]
    }}

If the model instead stops with a plain-text answer (`explain_only`), that text
becomes the summary and the episode converges without findings.

## Security

With no human preview by default, `allowed_tool_signatures` is the entire
security boundary — keep it as narrow as the task needs, and prefer read-only
signatures unless a write is genuinely required. See the interactive-actors
guide's Security section; the same reasoning applies here.

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*Consult [api-reference.md](api-reference.md) for complete listing*