loop_status

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

With no annotations the description carries the full burden, and it does disclose meaningful behavior: the journals it self-reads, that zero pending yields a quiet {count:0}, and that it only emits a hint to close decisions rather than closing them (implying non-mutating). It omits permission/auth requirements and any note on whether session state is written.

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?

One dense paragraph that front-loads the argument-free mode before the ledger mode, so the highest-frequency path is read first. It is efficient but jargon-heavy (emoji, mixed Russian field names) and could be split for faster scanning.

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 dual-mode session-state tool with no annotations and no output schema, the description covers both invocation paths and sketches the return payloads, which is enough to call it correctly. Remaining gaps are minor: exact hint text, decision_id semantics, and behavior on malformed ledger entries.

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 description coverage is 0%, so the description must compensate, and it does: the single ledger parameter is documented by shape [{decision_id,predicted,actual,endorsed}] and by effect (open/closed, prediction accuracy, share endorsed). That is more than the bare 'array' type in the schema, though field-level types and nullability remain undefined.

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 spells out two concrete behaviors: with no arguments it reads the principis.md and relationship.md journals and returns pending ⏳-decisions plus a hint; with a ledger it returns an open/closed summary plus prediction accuracy. That is a specific verb+resource pair, not a restatement of the name. It does not, however, distinguish itself from close-siblings like pending_outcomes or prediction_calibration, which appear to overlap with its two modes.

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 gives an explicit condition for each mode: no arguments = start of a new session, ledger supplied = summary mode. The agent knows which input selects which behavior. It stops short of naming alternatives or when-not to use it versus the many sibling outcome/calibration tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.