Skip to main content
Glama

repair_path

Read-onlyIdempotent

Find the shortest sequence of field changes taking invalid data to a valid state, as an ordered path of intermediate states. Different from repair (one-shot nearest fix): use repair_path to explain or audit the fix, or compare alternative repairs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
api_keyYesGeodesicAI API key (gai_...)
rank_byNoRanking criterion for returned pathsshortest
blueprintNoBlueprint name (workflow_name) to usedefault
max_depthNoSearch depth, 1-10
structured_dataYesThe document's extracted fields as key/value pairs. Keys are open by design - your Blueprint's rules define what is checked

TDQS

A4.4/5.0
Behavior4/5

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

The description discloses that this tool returns an ordered path of intermediate states rather than a single final state, and that it can be used to compare alternative repairs. Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered; the description adds the path-oriented behavior and the distinction from repair.

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

Conciseness5/5

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

The description is two sentences: the first states the core function, the second immediately distinguishes it from the sibling tool. Every phrase earns its place with zero wasted words.

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

Completeness4/5

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

The description covers the core purpose, usage context, and output type (ordered path), and the schema handles parameter details. However, because there is no output schema, the description could clarify the structure of the path (e.g., fields, step format) and the meaning of ranking criteria like 'drift' or 'risk' beyond enums. Still, given annotations and clear differentiation, it's reasonably complete.

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?

The schema provides descriptions for all 5 parameters, covering 100% of them, so the description doesn't need to elaborate. The description implies the tool operates on 'field changes' and 'invalid data', which aligns with the structured_data parameter, but doesn't add syntax or format details beyond the schema. Baseline 3 is appropriate.

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 uses a specific verb ('Find') and resource ('sequence of field changes') and clarifies it produces an ordered path of intermediate states. It explicitly distinguishes from the sibling tool 'repair' by name, making its purpose unambiguous.

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

Usage Guidelines5/5

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

The description gives explicit usage guidance: it says to use repair_path to explain or audit the fix, or compare alternative repairs, and contrasts it with repair, which provides a one-shot nearest fix. This clearly frames when this tool is preferred over the alternative.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.6/5.0
Disambiguation3/5

Most tools have distinct purposes, but several pairs overlap heavily (validate vs validate_repair, repair vs repair_path, analyze_anomaly vs check_drift vs decompose_failure). Detailed descriptions help disambiguate, but the large number of analytics and diagnostics tools creates real selection risk.

Naming Consistency4/5

The vast majority use a consistent snake_case verb_noun pattern (create_blueprint, list_api_keys, verify_certificate). A few single-word or noun-phrase exceptions (validate, forecast, structural_types, recent_inference_decisions) are minor deviations, but overall the pattern is predictable.

Tool Count2/5

At 37 tools, this exceeds the 25+ threshold for 'too many'. While the governance domain is broad, the set could be consolidated (e.g., merging validate_repair into validate, folding repair_path into repair, or trimming diagnostics-tier tools like check_realization and geometric_confidence).

Completeness4/5

The surface covers the full blueprint lifecycle, validation, repair, API key management, discovery, inference governance, and chain management. Minor gaps exist: no direct get_blueprint (only list with counts), and chain lifecycle lacks delete/list/cancel operations. Overall, agents can accomplish core governance tasks without dead ends.

Resources