A final job-specific fitting step that checks whether a tailored resume fits its allowed information and page budgets.

Use it after tailoring and validation to review ranked trimming options, choose changes, and produce the final resume.

It helps shorten or compress the resume when needed while protecting its claims, content record, and export validity.

perfect — Skill for Claude Code by dcassil/resume-kit

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add dcassil/resume-kit --skill perfect

Clone the repo

git clone --depth 1 https://github.com/dcassil/resume-kit

Made for: Claude Code.

Or install resume-intelligence, the plugin that ships this one along with the rest of its 31 skills, 1 command, 1 hook.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/dcassil/resume-kit/perfect/github.svg)](https://agentmods.dev/skills/dcassil/resume-kit/perfect)

Your own site

<a href="https://agentmods.dev/skills/dcassil/resume-kit/perfect"><img src="https://agentmods.dev/badge/skills/dcassil/resume-kit/perfect/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/dcassil/resume-kit/perfect"><img src="https://agentmods.dev/badge/skills/dcassil/resume-kit/perfect.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 58 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 772 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00058	$0.00772
Opus 5.5	$0.00023	$0.00309
Sonnet 5.5	$0.00012	$0.00154
Haiku 4.5	$0.00006	$0.00077

Measured 1mo ago against content hash d4a88c524968, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

perfect scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/resume-intelligence/skills/perfect/SKILL.md · 74 lines

How it starts

The opening of the file, as written. The whole thing — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.

perfect — final job-aware fit

Final step after tailoring and truth validation. This skill drives the deterministic fit capability, which checks the tailored resume against the shape policy's informational budgets, ranks trim/compression candidates against the active job, and writes the final resume only when the edit-session gate commits.

Prerequisites

Run the shared Prerequisites gate — ../_shared/prerequisites.md.

Required inputs: an initialized resume-kit/ project, a tailored ResumeDocument JSON for the job (normally the current active/resolved resume after update-keywords / update-terminology), and an active JobDescription JSON.
If no tailored resume exists: STOP and run the tailoring skills first (check-keywords, check-gaps, then update-keywords / update-terminology as needed).
If no active job exists: STOP and run parse-job first.
If the resume JSON is missing: STOP and run parse-resume first, then baseline and tailor before fitting.

What it does

Budget check. Run resume-tool fit --root . --job <job> to evaluate the resolved resume against the active job and current shape policy budgets.
Present ranked work. Show violations, ranked trim candidates, and compressions. Explain which items are deferred because they need judgment or failed a claim-preservation check.
Drive decisions. For the interactive path, use the existing edit-session decision UX to choose keep/drop/compress for the proposed changes. For the automated path, run resume-tool fit --root . --auto-fit.
Report final state. Show final_path, whether it committed, applied, deferred, and whether ledger_ok passed.

How to invoke

CLI

resume-tool fit --root . [--job <jobs/job.json>] [--output {json,text,md}]
resume-tool fit --root . [--job <jobs/job.json>] --auto-fit [--output {json,text,md}]

--job is optional when resume-kit/config.json already has active_job. --auto-fit uses ranked candidates to commit through the same edit-session gate. Without --auto-fit, present the ranked candidates and drive the user's decisions through the edit-session UX before committing.

Read the full file on GitHub · 74 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

1mo ago First seen · 74 lines · 58 tokens per session scan A d4a88c524968

Subscribe to this mod's changes

perfect is a skill published in the GitHub repository dcassil/resume-kit (0 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 58 tokens to every session and 772 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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