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by com.ksaworks
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Playlist Policy Open

playlist_policy_open
Read-only

Start or reuse one school's policy: its institution-wide rules, worked out once and used by every playlist at that school. Finds the school's captured pages that carry institution-wide rules, then answers hit (the stored policy, its policy_id and status), or stale or miss with a manifest of sections to read with playlist_read: award_types, policies, one page:<capture_file> for each qualifying page, and designations, each with its character count. On stale it also returns the stored policy, so you can see what changed. The server calls no AI model: you read the sections, reason over them yourself, and send the policy with playlist_policy_save.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "unitid": "<unitid>"
    },
    "name": "playlist_policy_open"
  }
}

Input Schema

NameRequiredDescriptionDefault
unitidYesThe school, by its IPEDS UNITID

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.4/5.0
Behavior5/5

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

Read-only annotation is already covered, but the description adds far more: three distinct outcome states (hit, stale, miss), what each returns, that stale includes the stored policy for comparison, that the manifest lists sections with character counts, and that no AI model is called. That is exactly the behavioral context an agent needs before deciding how to proceed.

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

Conciseness4/5

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

Purpose and outcome states are front-loaded, and every clause carries information about behavior or next steps. The middle enumeration of manifest sections makes it a long, dense sentence, but nothing is filler.

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 takes on the job of explaining returns, and it does: the hit/stale/miss states, manifest contents, character counts, and the stale payload. Combined with the explicit handoff to playlist_read and playlist_policy_save, an agent has everything needed to call it and act on the result.

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

Parameters3/5

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

There is only one parameter and the schema already documents it fully (IPEDS UNITID with an example). The description frames it as 'one school's policy' but adds no format or resolution detail beyond the schema, so baseline 3 applies.

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?

Names a specific verb (start or reuse) and resource (one school's institution-wide policy scope), and explicitly distinguishes this from playlist_read (section reading) and playlist_policy_save (writing the policy). An agent can tell exactly what this opens and what it is not.

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

Usage Guidelines4/5

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

Gives a clear workflow: open the policy, then read the listed sections with playlist_read and send the result with playlist_policy_save. It also maps outputs to next actions (hit = done, stale/miss = read sections). It stops short of stating when not to use this at all, which keeps it off a 5.

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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