The AGI-2027 Thesis Tracker: a single auditable 0-100 score of how much of Aschenbrenner's Situational Awareness thesis is holding up, with method and full score history.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It discloses the output includes a 0-100 score, methodology, and full history, which gives a good sense of what to expect. It does not mention read-only nature or limitations, but for a simple read operation this is adequate.
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 a single, well-structured sentence that packs in the key purpose, scope, score range, and included components. Every clause earns its place, with no redundancy.
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?
For a simple no-parameter tool, the description is complete: it explains what the score represents, the range, and ancillary information (method and history). It could mention return format, but the output schema is absent, so the description covers enough for an agent to invoke it confidently.
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 tool has 0 parameters, so the baseline is 4. The description doesn't need to add parameter semantics since there are none. It appropriately focuses on the output.
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 provides a single auditable 0-100 score for Aschenbrenner's Situational Awareness thesis, including method and history. This is a specific verb-resource pairing (get + thesis tracker) that distinguishes it from sibling tools about sunwatch or verdicts.
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 use when one needs the thesis tracker's current score or historical context. It does not explicitly mention alternatives, but the context of 'AGI-2027 Thesis Tracker' makes the use case clear, and no conflicting tools are suggested.
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 targets a distinct data source: market-call ledger, thesis score, prediction verdicts, and site search. The only slight overlap is between thesis_tracker and verdicts, but descriptions clearly separate them by content and purpose.
Three tools use the get_<object> pattern consistently with snake_case, but search_site uses a different verb. This is a minor deviation from an otherwise uniform naming convention.
With 4 tools, the server is tightly scoped to its purpose of exposing scorecard data and site search. There is no redundancy and the count is well within the ideal range for a focused server.
The server covers all core data endpoints (market calls, thesis score, verdicts) and includes site search for any additional content. As a read-only resource, there are no obvious missing operations or dead ends.