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Parse Standard Operating Procedure

parse_sop

Parse a Standard Operating Procedure markdown file from disk into a structured SopDocument, returning validation errors instead of raising when an existing file fails to parse.

Instructions

Parse a Standard Operating Procedure markdown file (YAML frontmatter + body) from disk into a structured :class:~biz.dfch.specmgr.sop.models.v1.SopDocument. An existing file that fails to parse returns a non-raising ValidateResult (valid=False, a single errors[].message capped at 300 chars as the generic validate tool caps it, feat-110) instead of raising AssertionError/pydantic.ValidationError/yaml.YAMLError (ADR f14f125e-eaad-4f4f-a6fd-3c931bed726e, GitHub issue #204 -- case 5 of the ADR 519d1206 non-raising-structured-result workaround chain); a truly-absent or unreadable path still raises the OSError-family file-access error (FileNotFoundError/PermissionError/OSError) from Path.read_text().

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.36.0

TDQS

A4.1/5.0
Behavior5/5

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

With no annotations present, the description carries the full behavioral burden and does so exceptionally: a parse failure on an existing file returns a non-raising ValidateResult (valid=False, errors[].message capped at 300 chars) rather than raising AssertionError/ValidationError/YAMLError, while an absent or unreadable path still raises the OSError family from Path.read_text(). This is exactly the raise-vs-return distinction an agent must know before calling.

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 core purpose is correctly front-loaded, but the single run-on sentence is bloated with internal identifiers (feat-110, ADR f14f125e..., GitHub issue #204, case 5 of the ADR 519d1206 chain) that add no actionable value for an agent. The genuinely useful behavioral content is buried inside that noise.

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?

For a one-parameter tool with an output schema, the description covers purpose, input source, return shape on both success and validation failure, and the raise boundary. Nothing an agent needs to call it correctly is missing.

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?

Schema description coverage is 0% for the single 'path' parameter, so the description must compensate. It does add meaning ('from disk', 'truly-absent or unreadable path', Path.read_text()), confirming path is a filesystem path to an existing file, but it gives no format details such as relative vs absolute or expected extension handling.

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?

States a specific verb (Parse), a precise resource (a Standard Operating Procedure markdown file with YAML frontmatter + body), and the source (from disk), plus the return type (SopDocument). The document-type qualifier cleanly separates it from the many parse_tsk/parse_gol/parse_req siblings without opening their schemas.

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?

Usage is only implied: the description makes clear this parses an on-disk file into a model, which differentiates it from get_sop/list_sop/create_sop in spirit, but it never explicitly says when to reach for parse_sop versus those siblings or state preconditions. An agent can infer the context but gets no routing guidance.

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