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save_snapshot

Save a concept-to-files map as a persistent project snapshot. Maps feature names and data flows to the files that implement them. Retained for direct maintenance of legacy maps; the managed map-build workflow has been removed.

Instructions

Save a concept-to-files map as a persistent project snapshot. Maps feature names and data flows to the files that implement them. Retained for direct maintenance of legacy maps; the managed map-build workflow has been removed. Persists across conversations — future sessions can call get_snapshot to instantly find relevant files. No API key needed — you are the LLM generating the map.

Input Schema

NameRequiredDescriptionDefault
dirYesAbsolute path to the project root directory
flowsYesMap of flow names to ordered file chains
featuresYesMap of feature names to their implementing files
removeFlowsNoFlow names to delete from the existing map. Applied before merging; only meaningful on incremental saves.
removeFeaturesNoFeature names to delete from the existing map — for features that were renamed or no longer exist. Applied before merging; only meaningful on incremental saves.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.22.0
    • changedInput schema / properties / features / additionalProperties / properties / type / description
      Previous value: -"Classification: \"capability\" for user-facing functionality, \"infrastructure\" for internal plumbing with no end user (DI/service wiring, config, logging, adapters). Capabilities are published to Confluence; infrastructure stays in the AI concept map only. Defaults to \"capability\"."New value: +"Classification: \"capability\" for user-facing functionality, \"infrastructure\" for internal plumbing with no end user (DI/service wiring, config, logging, adapters). Defaults to \"capability\"."
  2. Changed3 schema fields changedv0.17.0
    • addedInput schema / properties / features / additionalProperties / properties / type
      Added value: +{
+  "description": "Classification: \"capability\" for user-facing functionality, \"infrastructure\" for internal plumbing with no end user (DI/service wiring, config, logging, adapters). Capabilities are published to Confluence; infrastructure stays in the AI concept map only. Defaults to \"capability\".",
+  "enum": [
+    "capability",
+    "infrastructure"
+  ],
+  "type": "string"
+}
    • addedInput schema / properties / removeFeatures
      Added value: +{
+  "description": "Feature names to delete from the existing map — for features that were renamed or no longer exist. Applied before merging; only meaningful on incremental saves.",
+  "items": {
+    "type": "string"
+  },
+  "type": "array"
+}
    • addedInput schema / properties / removeFlows
      Added value: +{
+  "description": "Flow names to delete from the existing map. Applied before merging; only meaningful on incremental saves.",
+  "items": {
+    "type": "string"
+  },
+  "type": "array"
+}
  3. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It usefully adds persistence semantics ('Persists across conversations') and the surprising operational fact that no API key is needed because the caller is the LLM generating the map. However, it does not disclose whether a save overwrites or merges an existing snapshot, which is the critical behavioral trait for a write tool.

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 persistence are front-loaded, and the sentences are short and mostly non-redundant. The 'No API key needed — you are the LLM generating the map' clause is a slightly tangential framing statement but still informative, keeping it just below a perfect score.

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?

No output schema exists, so the description appropriately covers persistence and the downstream read path. It is nearly complete for a 5-parameter, nested-object write tool, with the only real omission being the overwrite-vs-merge behavior (partially hinted at by the schema's 'Applied before merging' notes).

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 100%, so every parameter (dir, features, flows, removeFlows, removeFeatures) is already documented in the schema, including nested fields and merge ordering. The description adds no parameter-level detail beyond the schema, so the baseline of 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?

The description names a specific verb and resource ('Save a concept-to-files map as a persistent project snapshot') and clarifies what the map contains (feature names and data flows mapped to implementing files). It also names its read-side counterpart get_snapshot, letting an agent distinguish it from siblings without opening a schema.

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?

It offers some context ('Retained for direct maintenance of legacy maps; the managed map-build workflow has been removed') and references get_snapshot as the downstream consumer. However, it never states an explicit when-to-use vs the other siblings (verify_snapshot, get_snapshot, save_decision) or prerequisites for calling it.

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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