Aztec Energy

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, so the safety profile is covered. The description adds real behavioral value by explaining what content the tool returns (per-energy source guidance) and why it matters, though it says nothing about output format or length, which is acceptable given an output schema exists.

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 purpose is front-loaded and every sentence carries information, but the full French/English duplication makes it longer than necessary for a one-paragraph guide. No filler or tautology, just some redundancy from bilingual restatement.

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 read-only guidance tool with a single optional enum parameter, an output schema, and annotations covering the safety profile, the description supplies everything needed: what it explains, when to invoke it, and its role in the heat-pump workflow. Return-value details are correctly delegated to the output schema.

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 100% and the single enum parameter is fully documented, so the baseline is 3. The description mentions the three energy sources implicitly (gaz, fioul, électricité), which loosely mirrors the enum, but adds no syntax or defaulting guidance 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 names a specific resource and action — a step-by-step guide to obtaining one's consumption statement — and explicitly scopes it to GRDF gas, Enedis/Linky electricity, and fuel-oil invoices. It also distinguishes itself from the sibling estimer_puissance_pac by naming that tool as the downstream consumer, so an agent can tell the two apart without opening schemas.

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 trigger conditions explicitly: use when the person does not have their statement, does not know where to find it, or asks how to download it. It also names the purpose in the workflow (input needed for heat-pump sizing), giving clear when-to-use context and a routing hint to the sibling.

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?

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), so the description only needs to add behavior. It does: results are indicative and based on the current barème, must be confirmed on france-renov.gouv.fr, and the reste à charge is returned only when a budget is supplied. It omits eligibility prerequisites (e.g. owner-occupier, dwelling age) and any input-validation behavior.

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?

Three sentences, front-loaded with the covered schemes and followed by the disclaimer; the bilingual duplication is mildly redundant but useful for retrieval. Nothing extraneous is present.

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?

An output schema exists, so return values need not be described. The description is nearly complete for a read-only estimation tool: it names the covered and non-covered aids and the confirmation source. It stops short of stating eligibility conditions or handling of missing/optional inputs.

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 100%, so the schema carries the per-parameter burden and the baseline is 3. The description adds real meaning by explaining the interaction between budget_travaux_eur and the computed reste à charge, and by tying revenu_fiscal_reference to the income category (catégorie de revenus) used by MaPrimeRénov'.

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 (estimate) and a precisely scoped resource: French national subsidies for an air/water heat pump, enumerating the schemes covered (MaPrimeRénov', CEE, TVA réduite, éco-PTZ). It is trivially distinguishable from the sibling estimer_puissance_pac, which sizes equipment rather than computing subsidies.

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?

Usage is implied (call this when you need aid amounts for a heat pump project) but there is no explicit when-to-use/when-not guidance and no reference to the sibling tool. The stated limits (amounts indicative, local aid not quantified) are scope disclaimers rather than routing guidance.

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?

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=true, so safety is covered; the description goes further by disclosing the mandatory-input failure mode (no consumption data → no figures, plus guidance on how to obtain it) and the output scope including a catalog-limited recommendation with the caveat that other models may fit. It does not describe runtime behavior, input-validation errors, or data-format failure handling beyond the missing-data case.

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?

Front-loading is good — purpose, then outputs, then the hard requirement, then use cases, then the disclaimer. But the entire content is stated twice (French then English), so roughly half the text is duplication that adds no information for a single-pass reader, and the parenthetical output list is dense.

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?

An output schema exists, so return values need not be explained, and the description covers everything else an agent needs: prerequisites, accepted input sources (GRDF/Enedis CSV, fioul deliveries, France-only scope), intended use cases, and accuracy limitations. Nothing material is missing for correct invocation.

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 100%, so the baseline is 3, and the description adds genuine cross-parameter meaning the schema does not: releve_consommation is 'indispensable pour gaz et électricité' while fioul uses livraisons_fioul (at least 3 deliveries), and code_postal drives local weather lookup. That conditional dependency is the main thing the flat schema cannot express.

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 names a precise verb and resource ('Dimensionnement d'une pompe à chaleur (PAC air/eau)') and enumerates the concrete outputs (bilan thermique, déperditions, puissance à la température de base, consommation électrique estimée, économie annuelle, modèle du catalogue). It is unmistakably about heat-pump sizing. It never names or contrasts the one sibling, estimer_aides, so differentiation is left to inference.

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 explicit when-to-use triggers ('quelle puissance de pompe à chaleur pour ma maison, remplacer une chaudière gaz, fioul ou un chauffage électrique, estimation avant la visite d'un installateur') and a hard prerequisite with its consequence ('Un relevé de consommation est NÉCESSAIRE : sans lui, l'outil ne donne aucun chiffre'). It also bounds the scope ('Estimation préliminaire : ne remplace ni la visite technique ni la note de dimensionnement de l'installateur'), so the agent knows when this tool is the wrong answer.

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