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ado_estimate_effort

Read-only

WHEN: user asks for an effort estimate, chiffrage, or development hours for a D365 Work Item. [~] PRIORITY TRIGGER: call AFTER ado_analyze_workitem when the user asks 'how long?', 'estimate this', 'chiffre ce WI'.

[t] EFFORT ESTIMATOR -- Estimate D365 F&O development effort for a Work Item. Uses KB signals (object count, method complexity, existing extensions, relation depth) combined with ADO history (similar past tasks) to produce a structured hour estimate broken down by phase: Analysis / Dev / Test / Deploy.

Returns:

  • Per-phase hour breakdown (table)

  • KB signals used (objects found, extensions, complexity flags)

  • Confidence level and risk factors

  • Ready-to-paste estimate for ADO task Original Estimate field

Triggers: 'estimate WI #N', 'how long for WI #N', 'chiffrage WI #N', 'effort estimate', 'combien de jours pour', 'combien d'heures pour'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectNoOptional: Azure DevOps project name. Falls back to DEVOPS_PROJECT env var.
workItemIdYesWork Item ID to estimate, e.g. 6587.
focusObjectsNoOptional: comma-separated D365 object names to force-include in analysis (speeds up estimation).

TDQS

A4.3/5.0
Behavior4/5

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

Annotations declare readOnlyHint=true, and the description adds useful behavioral context by explaining that the tool combines KB signals with ADO history and returns a phase breakdown, confidence level, and risk factors. It also notes the focusObjects parameter can speed up the estimate, which is beyond what the schema alone provides.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear sections (WHEN, PRIORITY TRIGGER, Returns, Triggers) and front-loads the core purpose. It is slightly redundant because trigger phrases appear both in the WHEN/PRIORITY TRIGGER section and in the final Triggers list, but the organized layout keeps it scannable and useful.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description compensates by explicitly listing return contents: per-phase hour breakdown, KB signals, confidence level, risk factors, and a paste-ready estimate. It covers key context like trigger conditions and sequencing with a previous analysis step. It does not describe error or edge-case behavior, but that is not critical for this read-only estimator.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, and each parameter already includes descriptive text (workItemId example, project fallback, focusObjects force-include behavior). The tool description adds little parameter-level meaning beyond the schema, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a precise verb and resource: 'Estimate D365 F&O development effort for a Work Item.' It clearly distinguishes itself from siblings by framing the output as a structured hour estimate with per-phase breakdown, not analysis, creation, or comment posting.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly tells the agent when to call it ('WHEN: user asks for an effort estimate...'), gives the priority sequencing ('call AFTER ado_analyze_workitem'), and provides concrete trigger phrases such as 'estimate WI #N', 'how long for WI #N', and 'chiffrage WI #N'. This is explicit, actionable usage guidance.

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

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TDQS

A4.1/5.0
Disambiguation4/5

Most tools have distinct purposes and clear triggers, reducing ambiguity. For example, PR-related tools are separated into analysis, listing, commenting, and dependency mapping. However, some overlap exists between find_references, find_extensions, and find_callers, which could confuse an agent without careful descriptions.

Naming Consistency4/5

Tool names follow a consistent snake_case pattern with verb_noun structure within subgroups (e.g., ado_*, find_*, search_*, generate_*). There is no mixing of camelCase or other styles, though the variety of prefixes slightly reduces predictability.

Tool Count3/5

With 38 tools, the server feels slightly over-scoped for its domain. While each tool has a specific function, the number is high compared to typical well-scoped servers (10-15 tools). Some tools like find_references and find_callers could be consolidated.

Completeness4/5

The tool set covers a broad range of D365 F&O development and DevOps tasks, including code search, analysis, security, performance, upgrades, and work item management. Minor gaps exist, such as the absence of direct object modification or batch job management, but the core workflows are well covered.