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Persistent Project Context for xAI Grok

Re-ground on .faf content (drift → refresh → re-grounded)

refresh_faf
Read-onlyIdempotent

Re-ground on .faf content — re-score via the Mk4 Zig-WASM Enterprise scorer (33-slot, honors the authored app-type shape), report drift vs an optional baseline score, and return a stamped re-ground. The explicit re-grounding primitive for long sessions: drift → refresh → re-grounded. Built for Grok, by request.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYesRaw .faf YAML content to re-ground on.
baselineNoOptional last-known score (0-100). When provided, the drift delta (current - baseline) is reported.
verbatimNoWhen true, return the full .faf content verbatim with the stamp. Default false (stamped delta + summary).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -{
      -  "properties": {
      -    "content": {
      -      "items": {
      -        "properties": {
      -          "text": {
      -            "description": "Human-readable tool result.",
      -            "type": "string"
      -          },
      -          "type": {
      -            "const": "text",
      -            "type": "string"
      -          }
      -        },
      -        "required": [
      -          "type",
      -          "text"
      -        ],
      -        "type": "object"
      -      },
      -      "type": "array"
      -    },
      -    "isError": {
      -      "description": "True when the tool failed.",
      -      "type": "boolean"
      -    }
      -  },
      -  "required": [
      -    "content",
      -    "isError"
      -  ],
      -  "type": "object"
      -}New value: +null
  2. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "properties": {
      +    "content": {
      +      "items": {
      +        "properties": {
      +          "text": {
      +            "description": "Human-readable tool result.",
      +            "type": "string"
      +          },
      +          "type": {
      +            "const": "text",
      +            "type": "string"
      +          }
      +        },
      +        "required": [
      +          "type",
      +          "text"
      +        ],
      +        "type": "object"
      +      },
      +      "type": "array"
      +    },
      +    "isError": {
      +      "description": "True when the tool failed.",
      +      "type": "boolean"
      +    }
      +  },
      +  "required": [
      +    "content",
      +    "isError"
      +  ],
      +  "type": "object"
      +}
  3. First observed

TDQS

A4.1/5.0
Behavior4/5

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

The description discloses several behavioral traits not present in the annotations: it re-scores with the 'Mk4 Zig-WASM Enterprise scorer (33-slot)', reports drift when a baseline is given, and returns a stamped re-ground. Annotations already cover readOnly, idempotent, and non-destructive, and the description does not contradict them.

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?

The description is compact and front-loaded, with the core functionality in the first sentence and the use-case framing in the second. There is some non-essential noise, such as 'Built for Grok, by request' and repeated 'drift → reflection → re-grounded' phrasing, but overall it remains informative without being bloated.

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?

Given three parameters and no output schema, the description still provides a fairly complete picture because the schema's verBatim description covers the output behavior. The 'drift vs baseline' and 'stamped re-ground' are sufficiently sketched for an agent to invoke the tool correctly, though terms like '33-slot' and 'Mk4 Zig-WASM Enterprise scorer' remain unexplained.

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 input schema already provides 100% description coverage for the three parameters, including optionality of baseline and the verbatim flag's effect. The tool description adds minimal new semantic value for parameters beyond restating 'optional baseline score' and 'stamped re-ground' without clarifying parameter formats or relationships.

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 states exactly what the tool does: 're-ground on .faf content' via re-scoring, reporting drift against a baseline, and returning a stamped re-ground. It uses a specific verb (re-ground) and resource (.faf content) and further distinguishes this as 'the explicit re-grounding primitive,' separating it from siblings like faf_score, faf_analyze, and delta_check.

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?

The description gives clear context for when to use the tool: 'for long sessions' and follows the 'drift → refresh → re-grounded' workflow. It doesn't explicitly list when not to use it or name alternative tools, but the positioning as the dedicated re-grounding primitive makes the main use case obvious.

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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TDQS

B3.3/5.0
Disambiguation2/5

Several faf_* tools overlap: faf_score, faf_validate, faf_analyze, and faf_gate all grade or gate content, while faf_get_tier and gf_analyze both address tier determination. Search and discovery also fragment into faf_collections_search, search_context, search_bfy_tag, list_tags, and tag_intel, making it easy for an agent to pick a nearly-equivalent tool.

Naming Consistency3/5

The set consistently uses snake_case and leans heavily on the faf_ domain prefix, but the style is not uniform: faf_score, faf_validate, and faf_estimate_tokens are action-based, while faf_memory, faf_section, and faf_gate are noun- or verb-like with less clear command intent. Overall still readable, but the pattern is mixed.

Tool Count3/5

19 tools is at the upper end of a reasonable number for a context/analysis system, especially with faf_ prefix family. However, some tools could be consolidated; faf_analyze overlaps faf_score+validate+get_tier, the several gone by explicit domain; several search/ag tools overlap, and the broad read-only surface leaves no obvious fns for create/update/delete operations.

Completeness2/5

This is a heavy read/analysis and scoring surface, but it lacks obvious write/update/delete primitives for persistent context entities. There are soul list/get and search tools, a faf generator, scoring/validation tools, and recommendations, but no create_soul, update_soul, delete_soul, or analogous persistent mutation operations for .faf/.fafm data. For 'persistent project context,' the set feels read-only and incomplete.