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paultaki
by paultaki

render_run_protocol

Read-onlyIdempotent

Converts a loop into an executable markdown run protocol: objective, actions, one-change-per-round rule, verification, stop conditions, budgets, risk gates, and a ready Claude Code prompt.

Instructions

Render a loop as an executable markdown run protocol an agent can follow directly: objective/done contract, allowed actions, one-change-per-round rule, the same verification every round, a durable state-file skeleton, stop conditions, budget, risk-colored approval boundary, proof format, and a paste-ready Claude Code prompt. Session loops get bounded rounds; scheduled-tick business loops (SEO, ads, product metrics) get experiment logs, undo-losers discipline, and notify-the-human ticks.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
goalNoOptional operator goal to embed in the protocol
kindNoauto infers from the loop's trigger; override to force a session or tick protocolauto
id_or_slugYesLoop id or title
max_roundsNoSession loops: round budget
max_minutesNoSession loops: time budget
risk_postureNostrict treats every shared-surface action as approval-gateddefault
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint and idempotentHint, so the description adds value by detailing behavioral traits: different protocol structures for session vs. scheduled-tick loops, inclusion of risk-colored approval boundaries, budget constraints, and state-file skeletons. This goes beyond what annotations provide.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is comprehensive but verbose, with a long list of protocol components packed into a single paragraph. It front-loads the main purpose but could be more concise by grouping or shortening the enumerated items. Adequate but not minimal.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description fully explains what the rendered protocol contains (objective/done contract, allowed actions, verification rules, state-file skeleton, stop conditions, budgets, etc.). It covers behavioral differences based on loop kind, making it complete for an agent to understand and use the tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, but the description adds meaning by explaining how the 'kind' parameter affects the output (bounded rounds for sessions, experiment logs for scheduled-ticks) and how 'risk_posture' changes approval gating. This contextualizes parameters beyond enum labels and defaults.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states the tool renders a loop as an executable markdown run protocol an agent can follow, with a specific verb and resource. It distinguishes from sibling tools like get_loop or search_loops by focusing on generating an actionable protocol rather than retrieving or designing loops.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context (e.g., when an agent needs to execute a loop), but it does not explicitly state when to use this tool versus alternatives like get_loop or design_loop. No exclusions or direct comparisons are provided, leaving the agent to infer the appropriate use case from the description.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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