Match bank statement lines against unreconciled Xero transactions. Returns confidence-scored matches (>=0.8 matched, 0.5-0.8 suggested, <0.5 unmatched).
| Name | Required | Description | Default |
|---|---|---|---|
| to_date | No | End date filter (YYYY-MM-DD) | |
| from_date | No | Start date filter (YYYY-MM-DD) | |
| api_key_hash | Yes | Customer API key hash identifying Xero token |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses key behavioral traits by specifying confidence-scored output categories ('>=0.8 matched, 0.5-0.8 suggested, <0.5 unmatched'). This is valuable beyond the schema. It does not state whether the tool is read-only or has side effects, but given its matching/suggestion nature, this is a minor gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the primary purpose, and the second sentence explains the output categories. Every word earns its place; there is no redundancy or unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description explains what the tool does and its output format, but it does not clarify how bank statement lines are supplied (e.g., fetched automatically based on date range) or whether the operation has side effects. Given the absence of an output schema and annotations, this is a notable gap, so a score of 3 reflects the missing context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds meaning by clarifying that the tool operates on bank statement lines and Xero transactions, which helps interpret the to_date and from_date parameters as applying to bank statement lines. This contextual enrichment justifies a score above baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Match bank statement lines against unreconciled Xero transactions.' This uses a specific verb and resource, and the addition of 'Returns confidence-scored matches' further clarifies the output, distinguishing it from sibling tools like confirm_reconciliation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool—when there are bank statement lines to reconcile against unreconciled Xero transactions. It implicitly suggests this is for generating match suggestions, not finalizing them. However, it does not explicitly mention alternatives or exclusions, so it stops short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose, with complementary pairs like categorise_expenses (suggest) and apply_categories (apply), reconcile_transactions (match) and confirm_reconciliation (apply). No two tools appear to do the same thing.
Most tools follow a consistent verb_noun pattern (e.g., calculate_vat, draft_invoice, send_invoice), but 'health' deviates by being a plain noun, and there is a minor British/American spelling variation ('categorise' vs 'calculate').
9 tools is well-scoped for an accounting MCP, covering VAT calculation, categorization, reconciliation, invoicing, reporting, and health checks without redundancy or bloat.
Core workflows are well-covered, especially the propose/apply pairs for categorization and reconciliation. Minor gaps include lack of invoice read/update actions and no explicit transaction listing, but these are not critical given the server's focus.