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

With no annotations, the description carries the full burden. It usefully discloses the destructive scope ('all locally stored fills') and the confirmation guard, but says nothing about irreversibility, whether the operation can be undone, or any auth requirement.

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?

Two short sentences, destructive scope front-loaded, no filler. Every clause earns its place.

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 destructive tool with no output schema, the description covers what is deleted and the guard condition. The main remaining gap is the irreversibility/recovery behavior, which an agent might reasonably want before calling a delete-all tool.

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 0% and the schema only shows `confirm` with a default, so the description meaningfully adds the semantic requirement that confirm must be true to proceed. It doesn't clarify what happens if confirm is false, but there is only one parameter.

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?

Specific verb (delete) and resource (locally stored fills) with a clear scope qualifier ('all locally stored'). An agent can distinguish it from list_trades or import_fills, though the description never names those siblings explicitly.

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 states the precondition 'Requires confirm=true', which is genuine usage guidance, but gives no when-to-use framing (e.g., before re-importing fills) or warning about when not to use it.

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

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

With no annotations, the description carries the full burden and discloses little: it confirms the input date format (YYYY-MM-DD) but says nothing about whether periods are inclusive, whether A is the baseline, how deltas are reported, or what data must exist first. For a 4-parameter analytical tool this is a thin disclosure.

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?

A single front-loaded sentence with the core operation first, the format constraint second, and a concrete example last. Nothing is padded or redundant.

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?

No output schema and no annotations, so the description is the only source of context, yet it never says what 'stats' are returned, how the two periods are presented, or what happens on empty ranges. For a comparison tool with four required inputs this leaves material gaps.

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% and the properties carry only titles like 'A Start', so the description must compensate. It does add real meaning by mapping the four params to two periods and fixing the date format, but it never clarifies inclusivity of start/end or the direction of the comparison.

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?

States a specific verb (compare) and resource (stats) scoped to two named periods, with an example. It is distinguishable from siblings like get_stats by the two-period comparison framing, but it never names an alternative to contrast against, so it stops short of a 5.

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 'last week vs this week' example implies the intended use case, but there is no explicit statement of when to pick this over get_stats or any prerequisite (e.g. data must already be imported). Usage is implied rather than stated.

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

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

No annotations are present, so the description carries the full disclosure burden. It does convey that this is a purely descriptive analysis rather than an advisory or mutating operation, but it omits read-only confirmation, prerequisites (imported trade data), and error/empty-data behavior. Partial disclosure against a zero-annotation baseline.

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?

A single sentence, front-loaded with the action verb and scope, followed by the analytical dimensions and the constraint. No filler, no restatement of the tool name.

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?

With no annotations and no output schema, the description should explain the time-range parameters and the data prerequisite. The analytical coverage is well specified, but what the tool returns and how the start/end window governs the analysis are left unstated.

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 0% and neither 'start' nor 'end' has a title description, leaving both parameters semantically dark. The description never mentions a date range at all, so it does not compensate for the schema gap — the agent must guess what the two string params mean and whether empty defaults mean 'all data'.

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?

States a specific verb ('Describe') and a precisely scoped resource ('where the user's own past results were weakest'), then enumerates the exact dimensions analyzed (time of day, hold time, sizing after a loss). This is far more specific than siblings like get_stats, although no sibling is named explicitly to force the routing choice.

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?

'Descriptive findings only, never trade advice' sets a clear behavioral boundary on how results may be used, but the description never says when to pick this over get_stats or compare_periods, nor what data/period is required first. Usage is implied by the enumerated leak categories rather than stated.

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

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

No annotations are provided, so the description must carry the behavioral burden. It discloses the computed return values (useful given no output schema) and implies a read-only aggregation, but says nothing about data scope (which account), preconditions such as needing imported fills first, or cost/latency.

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?

A single front-loaded sentence; the metric list is long but earns its place since there is no output schema to document the return shape. Slightly dense, but no filler.

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?

Given no annotations, no output schema, and an undocumented 2-param schema, the description covers the return metrics well but leaves data-source scope (all trades vs a filtered set) and prerequisites unstated. Adequate but with clear gaps for a stats tool.

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 0%: start/end have no descriptions and empty-string defaults. The description partially compensates by stating the format (YYYY-MM-DD) and that both are optional, but omits range inclusivity (inclusive/exclusive) and what an empty value means (all time).

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?

Names a specific verb+resource ('Stats for closed round trips') and enumerates the exact metrics computed (net P&L, win rate, profit factor, max drawdown, etc.), so an agent knows precisely what comes back. It does not, however, distinguish itself from siblings like compare_periods or find_leaks.

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 parenthetical 'optionally between start/end YYYY-MM-DD' implies the date-range use case, so usage is inferable. There is no explicit guidance on when to prefer this over compare_periods or what happens if the range is omitted, leaving the agent to infer.

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

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

With no annotations, the description carries the full burden and does meaningful work: it discloses the persistence location (~/.tapelog/fills.json) and that duplicates are skipped, both non-obvious behaviors implying merge-style idempotency rather than overwrite. It omits error behavior on malformed CSVs and what is returned after import.

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?

Four tight sentences, front-loaded with the supported formats and ending with storage/dedup semantics. Every clause conveys operational information; nothing is redundant.

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 4-parameter import with no annotations and no output schema, the description is nearly complete: inputs, format-specific date handling, and storage/dedup behavior are all covered. The one real gap is the undocumented 'broker' parameter and any indication of what a successful import reports back.

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. It explains csv_text, file_path, and trade_date (including the YYYY-MM-DD format), but the 'broker' parameter is never mentioned despite defaulting to 'auto', leaving a meaningfully undocumented knob for ambiguous inputs.

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?

States a specific verb ('Import executions') plus the concrete resources it accepts: DAS Trader Trades-window CSV, Robinhood activity CSV, or generic CSV with an explicit column list. This clearly separates it from the read/analysis siblings (get_stats, find_leaks, list_trades) and the destructive clear_data.

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?

Explicitly tells the agent which input channel to use (csv_text vs file_path) and gives a conditional rule for when trade_date is required ('DAS exports have no date: pass trade_date'). No explicit when-not-to-use guidance, but the format routing is unusually concrete.

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

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

No annotations are provided, so the description carries the full behavioral burden. It discloses the sort order but says nothing about whether the result is paginated, how start/end constrain the window, defaults, or whether it is a pure read — significant gaps for a listing tool with zero annotation coverage.

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?

A single short sentence, front-loaded with the verb and resource, with no filler. It is appropriately tight, though its brevity edges toward under-specification rather than efficient concision.

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?

With three undocumented parameters, no output schema, and no annotations, the description leaves the agent guessing what a 'round trip' contains and how the window parameters behave. It is not complete enough for a filtered list tool of this shape.

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%: 'start', 'end', and 'limit' have no documentation anywhere, and the description never mentions them. The ordering hint weakly implies a limit/recent-window concept, but the date-range semantics of start/end are entirely absent.

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 states a specific verb and resource ('List reconstructed round trips') and adds a useful ordering detail ('most recent first'). It is clearly distinct from get_stats, find_leaks, and compare_periods, though it never explicitly contrasts itself with those siblings.

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?

There is no statement of when to use this tool versus the alternatives (e.g., find_leaks for anomalies, get_stats for aggregates). The only guidance is implicit in the word 'trades' and the ordering note, which is not enough to route an agent reliably.

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