get_pnlFREE (operator). Summarize revenue (inbound), COGS (outbound), markup transfers, and gross profit from the cashflow ledger.
| Name | Required | Description | Default |
|---|---|---|---|
| since | No | Optional ISO timestamp — only include entries at/after this time |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description is the sole source of behavioral information. It states the tool is FREE and summarizes from the cashflow ledger, but it does not disclose side effects, required permissions, rate limits, return format, or whether it is strictly read-only.
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 concise and well-structured, packing the tool's main purpose, output components, and source into a single sentence without unnecessary fluff or repetition.
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 names the expected output components (revenue, COGS, markup transfers, gross profit) and the data source (cashflow ledger), giving the agent enough context to call the tool. It lacks an explicit output schema or details about edge cases, but the core context is present.
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?
The only parameter, `since`, is already documented in the schema as an optional ISO timestamp filter. The tool description adds no additional meaning beyond the schema, so parameter semantics are adequate but not enhanced.
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 purpose: to summarize PnL from the cashflow ledger, listing the specific components it computes (revenue, COGS, markup transfers, gross profit). This distinguishes it from related tools like get_cashflow, which likely return raw ledger entries.
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 implies the tool should be used when a PnL summary is needed, and mentions it is FREE and operator-scoped. However, it does not explicitly state when to prefer this over get_cashflow or other alternatives, so the usage guidance is only implied.
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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The core dispatcher tools are distinct, but the 84 auto-discovered wrappers contain dozens of near-identical news, weather, and translation endpoints. An agent cannot reliably tell many of these apart without reading provider-specific details, and misselection is likely.
Core tools use a readable verb_noun pattern, but most tools are machine-generated `x402_<domain>_<path>_<number>` names with opaque numeric suffixes. The two naming schemes are mixed, and the generated names are not intuitive.
95 tools is an extreme mismatch for a coherent MCP surface. The bulk are auto-registered third-party proxies that duplicate the same few categories, creating massive prompt bloat and selection overhead.
For an x402 dispatcher, the core lifecycle is well covered: discovery, search, quote, route-and-call, stats, paywall status, and cashflow/P&L. Minor gaps such as no deregistration or detailed per-transaction drill-down exist, but main workflows do not dead-end.