atlas-brief-mcp

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atlas_sheet_append

Append a new row to a spreadsheet tab by mapping column header names to values, validating headers before writing and verifying the entry by read-back. Use it to add new item or parameter rows.

Instructions

Append a new row to a spreadsheet tab by mapping column header names to values.

Use this tool when adding a new entry (e.g. a new unit, item, or parameter row) to a bound spreadsheet.
To modify cells of an existing row, use `atlas_sheet_update` instead.

Behavior & Output:
- Not idempotent: each non-dry-run call appends a new row at the bottom of the table and verifies it by read-back.
- Validates all keys in `values` against the tab's header row before writing.
- Returns JSON `{ok, sheet, tab, values, range, verified, resynced, dry_run}` and updates the local search index.

Input Schema

Name	Required	Description
`tab`	Yes	Exact worksheet/tab name inside the spreadsheet (e.g. 'Units'). Use `atlas_sheets` to discover valid tab names.
`sheet`	No	Optional spreadsheet name or ID when multiple spreadsheets are bound to the project.
`values`	Yes	Mapping of `{column_header_name: value}` for the new row (e.g. `{"ID": "monster_goblin", "Name": "Goblin", "HP": 100}`). Omitted columns are left empty.
`dry_run`	No	If true, validate column headers and preview the row without writing to the spreadsheet (default false).

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed6 schema fields changedv0.1.1Nov 6, 2026

addedInput schema / properties / dry_run / description

Added value: +"If true, validate column headers and preview the row without writing to the spreadsheet (default false)."

addedInput schema / properties / sheet / description

Added value: +"Optional spreadsheet name or ID when multiple spreadsheets are bound to the project."

addedInput schema / properties / tab / description

Added value: +"Exact worksheet/tab name inside the spreadsheet (e.g. 'Units'). Use `atlas_sheets` to discover valid tab names."

addedInput schema / properties / tab / minLength
```
Added value: +1
```

changedInput schema / properties / values / additionalProperties

Previous value: -trueNew value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "integer"
+    },
+    {
+      "type": "number"
+    },
+    {
+      "type": "boolean"
+    },
+    {
+      "type": "null"
+    }
+  ]
+}

addedInput schema / properties / values / description

Added value: +"Mapping of `{column_header_name: value}` for the new row (e.g. `{\"ID\": \"monster_goblin\", \"Name\": \"Goblin\", \"HP\": 100}`). Omitted columns are left empty."

First observedv0.1.0Nov 5, 2026

TDQS

A4.6/5.0

Behavior4/5

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

Goes beyond the annotations by disclosing that keys are validated against the tab's header row before writing, that each append is verified by read-back, and that the local search index is updated — none of which the annotations convey. The non-idempotency claim duplicates `idempotentHint: false`, though it usefully explains the consequence (a new row at the bottom per call).

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?

Front-loaded purpose sentence, then a usage sentence with the alternative, then a compact labeled behavior section — easy to scan and every line is substantive. The explicit return-key list is mildly redundant given that an output schema exists, but it earns partial credit by naming the meaningful flags (`verified`, `resynced`).

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 4-parameter mutation tool with full schema coverage, rich annotations, and an output schema, the description covers purpose, selection criteria, validation constraints, side effects (index update), and safety via dry-run. No gap remains that would cause a misinvocation.

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

Parameters4/5

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

Schema coverage is already 100%, so the 3 baseline is met; the description adds a real constraint not stated in the schema — that `values` keys are validated against the tab's header row before writing, which tells the agent keys must be exact header names. It also reinforces the header-name mapping model with a concrete conceptual example.

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 and resource (append a new row to a spreadsheet tab) plus the mechanism (mapping column header names to values). It explicitly contrasts with the sibling `atlas_sheet_update`, so an agent can distinguish the two without opening either schema.

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?

Gives an explicit when-to-use condition (adding a new entry such as a unit, item, or parameter row to a bound spreadsheet) and an explicit when-not with a named alternative (`atlas_sheet_update` for modifying existing rows). Nothing is left to inference.

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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