learn-terminology

learn-terminology is a skill for Claude Code from dcassil/resume-kit. It costs 123 tokens per session (2,760 once invoked), scanned A, original, Apache-2.0.

A workflow for teaching the resume matcher that two different terms mean the same skill. An alias is an approved alternative name, such as two phrases used for the same technology or responsibility.

In plain words
What is it for?
Use it to propose, verify, approve, and save project-specific terminology aliases so future resume-to-job matching can recognize them.
Why use it?
A deterministic matcher follows known terms and may mark a requirement missing when the resume uses different wording. This workflow adds an alias only after it passes a truth check and the user confirms it.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions subagents.

Part of the resume-intelligence plugin — 31 skills, 1 command, 1 hook shipped together

Good fit Use it to propose, verify, approve, and save project-specific terminology aliases so future resume-to-job matching can recognize them.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/dcassil/resume-kit/learn-terminology
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 learn-terminology
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.

agentmods badge for learn-terminology

README.md
[![agentmods](https://agentmods.dev/badge/skills/dcassil/resume-kit/learn-terminology.svg)](https://agentmods.dev/skills/dcassil/resume-kit/learn-terminology)
Your own site
<a href="https://agentmods.dev/skills/dcassil/resume-kit/learn-terminology"><img src="https://agentmods.dev/badge/skills/dcassil/resume-kit/learn-terminology.svg" alt="Measured on agentmods" height="20"></a>
Per session 123 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,760 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00123 $0.02760
Opus 5 $0.00062 $0.01380
Sonnet 5 $0.00025 $0.00552
Haiku 4.5 $0.00012 $0.00276

Measured 7d ago against content hash d15f393b12e9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

learn-terminology 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 7d 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/learn-terminology/SKILL.md · 240 lines

How it starts

The opening of the file, as written. The whole thing — 240 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Renamed: learn-terminology was manage-synonyms before v1.0.0 (see RIT-A-0005).

learn-terminology — propose → truth-gate → confirm → append aliases

Purpose

check-keywords and check-gaps score a resume against a job deterministically — no LLM at scoring time. Matching uses a packaged seed lexicon UNIONed with an optional project alias file (resume-kit/learning/synonyms.json, RIT-T-0068 format). When a scoring run marks a job keyword as "missing" but the resume already demonstrates that exact skill under a different name, the deterministic engine simply doesn't know the two terms are the same thing yet.

This skill is the agent-side growth loop that teaches it: the agent PROPOSES a synonym, the user CONFIRMS it, and the agent APPENDS a justified alias to the project file. From then on the deterministic run matches it — no LLM required at scoring time, ever. The agent only writes data; it never makes scoring smarter at runtime.

Define the workflow ONCE (here) so the three scoring skills link to it rather than copy-pasting divergent copies.

Automatic accepted-edit growth

The edit-session commit path also self-heals the same project alias file for a narrow, already-confirmed case: when the user accepts or edits a terminology proposal that mirrors the employer's wording, commit-session derives the token swap and appends the project alias automatically with source: "accepted_edit" provenance and the caller-supplied timestamp. Rejected, skipped, undone, auto-mode, non-terminology, malformed, and empty mappings do not grow aliases.

That automatic path complements this skill; it does not replace it. Use this manual workflow when a scoring run reports a missing keyword and no accepted terminology edit exists yet. The manual path still requires truth-gating and explicit user confirmation before writing.

Run me in a subagent

This is a self-contained, file-mutating task. The main agent should dispatch it to a subagent (e.g. the Task tool / a general-purpose agent), consistent with parse-resume and parse-job. Hand the subagent: the list of candidate (missing job keyword, resume term it may equal) pairs, the path to resume-kit/config.json, and this skill. The subagent runs the gate, gets user confirmation, appends → and returns only what it added (canonical, alias, why) plus what it rejected/deferred. Do NOT stream the full resume/job text back into the main context.

Read the full file on GitHub · 240 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.

  1. 7d ago First seen · 240 lines · 123 tokens per session scan A d15f393b12e9

Subscribe to this mod's changes

learn-terminology is a skill published in the GitHub repository dcassil/resume-kit (0 stars, last pushed 27d ago), licensed Apache-2.0. It adds 123 tokens to every session and 2,760 once invoked, about $0.0006 per session on Opus 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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