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Maestro Career Studio

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Rebuild Tailored Resume

tailor_application
Destructive

Apply typed edits to your base resume to create a job-specific application draft, replacing any prior tailored version.

Instructions

REBUILD FROM SCRATCH: apply typed edit ops to the BASE resume and store the result as customized_json, REPLACING whatever was there before wholesale.

`ops` carry only the changed fields (same op shapes as edit_base_resume; the
base is in get_base_resume) — the server starts from the stored base and
inherits every untouched field from IT, not from any prior tailored draft.
If an application already has tailored edits (from a previous tailor_application
or edit_application call), calling this again DESTROYS them — the new result is
computed fresh from the base, not layered on top. edit_application is the
in-place alternative that preserves the current tailored draft (refining
wording, swapping a bullet, retrying after a PDF preview).
Does NOT trigger AI suggestions. A job has one application: with no application_id,
the job's newest is updated in place and takes this base (still replaced wholesale);
pass application_id to target a specific application explicitly. `ops` accepts
the FULL vocabulary documented on edit_base_resume — every kind, not just
the bullet/summary ones: replace_entry is how you change an entry's dates, title,
company or tech list, and add/replace/remove/move_extra_section handle custom
sections, which are ATS-neutral.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
opsYesTyped edit ops. Each is an object with a `kind`, one of: replace_summary | toggle_entry | replace_bullet | replace_skills_group | add_skill_item | add_bullet | add_entry | replace_entry | remove_entry | remove_bullet | replace_contact | replace_certifications | add_extra_section | replace_extra_section | remove_extra_section | move_extra_section. To change a field ON an entry — dates, title, company, project name, link, tech — use replace_entry with that entry's index and the full edited entry object; it is scoped to that one entry (a whole-resume replace is the separate update_base_resume tool). See the tool description for each op's shape. add_extra_section/replace_extra_section `value` is {key,title,enabled,type:"entries"|"bullets"} plus EITHER entries:[{heading,subheading?,location?,date?,link?,enabled,bullets:[str]}] OR bullets:[str] — never both; unknown keys are rejected (400, extra="forbid").
job_idYes
base_resumeYes
application_idNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.11.1

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare destructiveHint=true and idempotentHint=false, but the description adds substantial non-obvious context: prior tailored edits are DESTROYED, the result is computed fresh from the base rather than layered, untouched fields inherit from the base not a prior draft, and it does NOT trigger AI suggestions. This goes well beyond the annotation flags, though it doesn't cover return shape or error behavior.

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?

Front-loaded with the core destructive action, then alternatives, then parameter behavior. It is long and caps-heavy, but nearly every sentence carries distinct information (destruction, inheritance, alternative, op vocabulary). Slightly dense.

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?

For a destructive, no-output-schema mutation tool, the description covers destruction semantics, inheritance behavior, the in-place alternative, and the full op vocabulary. The main residual gap is what base_resume expects, which matters for a required parameter.

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

Parameters4/5

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

With only 25% schema coverage, the description carries real weight: it explains the ops vocabulary ('FULL vocabulary documented on edit_base_resume'), op shapes, and application_id/job_id targeting semantics. However, the required base_resume string parameter is never explained (id? name? content?), leaving one of four params under-specified.

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?

States a specific verb and resource with scope: 'apply typed edit ops to the BASE resume and store the result as customized_json, REPLACING whatever was there before wholesale.' It explicitly distinguishes itself from edit_application (in-place) and edit_base_resume (base editing), so an agent can route correctly 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.

Usage Guidelines5/5

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

Gives explicit when-to-use vs alternative: 'edit_application is the in-place alternative that preserves the current tailored draft (refining wording, swapping a bullet, retrying after a PDF preview).' It also names when-not: calling again destroys prior edits, and explains application_id targeting vs the no-id default.

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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