Fork a live flock session from an existing trace: the server re-simulates the trace to its at_tick over the verified path and hands you the session at exactly that point, so you can continue where the author stopped. Same 10-second budget as trace verification. What happens just past the tick where they stopped looking?
| Name | Required | Description | Default |
|---|---|---|---|
| trace_id | Yes | 21-char trace id |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / trace_id / descriptionAdded value: +"21-char trace id"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It discloses that the server re-simulates the trace, follows the verified path, freezes the session at the trace's at_tick, and applies the same 10-second budget as trace verification. This is meaningful behavioral detail beyond the schema.
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 first sentence is tightly packed and front-loaded, and the budget note is useful. However, the final rhetorical question, 'What happens just past the tick where they stopped looking?' adds no operational value for an agent selecting or invoking the tool.
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 single-parameter tool with no output schema, the description covers the operation, purpose, mechanism, and a key timeout constraint. It leaves minor gaps around exact return shape and failure behavior, but the agent has enough to invoke it correctly.
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 input schema already fully documents the single required trace_id parameter, so the description does not need to add much. It implicitly associates the trace_id with the 'existing trace,' but adds no new format or usage details beyond the schema.
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 opens with a specific verb and resource: 'Fork a live flock session from an existing trace.' It explains the mechanism, mentions the at_tick target, and distinguishes itself from ordinary flock creation by emphasizing continuation from a verified trace.
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?
It clearly states the intended use case: continue where the author stopped by re-simulating an existing trace. It does not explicitly name alternatives such as flock_create for blank sessions, so it stops short of full when-not guidance.
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.
Most tools are cleanly separated by resource prefix (flock_, experiment_, trace_, proposal_) and action, so an agent can usually tell them apart. The main ambiguity is between experiment_run/experiment_get and the flock_* session tools, since both drive the same four-weight simulation; the descriptions mitigate this by framing experiment_run as the one-call batch alternative.
The dominant pattern is <resource>_<action> with readable verbs like create, get, step, browse, submit, and leave, and each resource family is internally consistent. Minor outliers like playground_manifest and what_changed don't follow the verb_noun convention, and browse/get both appear for retrieval, so the naming is mostly consistent but not uniform.
At 15 tools the set sits at the upper edge of the normal range, and the breadth is justified by the playground's dual simulation/experiment and community (traces/proposals) surfaces. It isn't bloated, but the experiment_* pair partially overlaps the flock_* session workflow, making the set feel slightly larger than strictly necessary.
The main lifecycle is covered: run/get for experiments, create/step/get/set_params/timeline for flocks, browse/get/leave for traces, and browse/submit for proposals, with manifest and what_changed orienting returning agents. Minor gaps exist—no experiment or flock listing endpoint and no proposal detail/withdraw tool—but discovery is handled through traces and what_changed, so agents can still complete workflows.