"algo-hr-matching"

"algo-hr-matching" is a skill for Claude Code from charlieviettq/awesome-agent-skill. It costs 68 tokens per session (876 once invoked), scanned A, a copy of algo-hr-matching, MIT.

An implementation of the Gale–Shapley method for matching two groups, such as applicants and jobs, using ranked preferences. It finds a stable result where no unmatched pair would both prefer each other.

In plain words
What is it for?
Use it to match candidates with positions, students with schools, or residents with hospitals when both sides rank their choices.
Why use it?
It helps avoid unfair or unstable assignments caused by matching people independently. The side that makes proposals gets its best possible result among all stable matchings.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Good fit Use it to match candidates with positions, students with schools, or residents with hospitals when both sides rank their choices.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/charlieviettq/awesome-agent-skill/algo-hr-matching
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 charlieviettq/awesome-agent-skill --skill algo-hr-matching
Clone the repo
git clone --depth 1 https://github.com/charlieviettq/awesome-agent-skill

Made for: Claude Code.

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 "algo-hr-matching"

README.md
[![agentmods](https://agentmods.dev/badge/skills/charlieviettq/awesome-agent-skill/algo-hr-matching/github.svg)](https://agentmods.dev/skills/charlieviettq/awesome-agent-skill/algo-hr-matching)
Your own site
<a href="https://agentmods.dev/skills/charlieviettq/awesome-agent-skill/algo-hr-matching"><img src="https://agentmods.dev/badge/skills/charlieviettq/awesome-agent-skill/algo-hr-matching/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.

agentmods 80×15 button for "algo-hr-matching"

Your own site · 80×15
<a href="https://agentmods.dev/skills/charlieviettq/awesome-agent-skill/algo-hr-matching"><img src="https://agentmods.dev/badge/skills/charlieviettq/awesome-agent-skill/algo-hr-matching.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 68 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 876 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 95% copy Near-identical to another mod 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 $0.00068 $0.00876
Opus 5 $0.00034 $0.00438
Sonnet 5 $0.00014 $0.00175
Haiku 4.5 $0.00007 $0.00088

Measured 12d ago against content hash a2aed3a9fb45, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

"algo-hr-matching" 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 12d 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.

Origin

This is a copy

95% identical to algo-hr-matching — 8 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.claude/skills/algo-hr-matching/SKILL.md · 86 lines

How it starts

The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Gale-Shapley Stable Matching

Overview

Gale-Shapley (deferred acceptance) finds a stable matching between two equally-sized sets where no unmatched pair prefers each other over their current match. Runs in O(n²) worst case. Proposer-optimal: the proposing side gets their best stable partner.

When to Use

Trigger conditions:

  • Matching candidates to job positions based on mutual preferences
  • Assigning students to schools or residents to hospitals
  • Any two-sided matching where stability (no blocking pairs) is required

When NOT to use:

  • For one-sided assignment (use Hungarian algorithm)
  • When preferences are based on scores, not rankings (use optimization)

Algorithm

IRON LAW: The Proposing Side Gets Their BEST Stable Partner
Gale-Shapley is proposer-optimal and reviewer-pessimal. If employers
propose, they get their best stable match; candidates get their worst.
The CHOICE of who proposes determines which stable matching is found.

Phase 1: Input Validation

Collect: preference rankings from both sides. Each participant ranks all members of the other side. Gate: Complete preference lists, equal-sized groups (or handle unequal with dummy entries).

Phase 2: Core Algorithm

  1. All proposers are "free" (unmatched)
  2. While any proposer is free and hasn't proposed to everyone:
    • Free proposer proposes to their highest-ranked unproposed-to reviewer
    • Reviewer accepts if unmatched, or replaces current match if new proposer is preferred
    • Replaced proposer becomes free again
  3. Terminate when all proposers are matched

Phase 3: Verification

Check stability: for every unmatched pair (a,b), verify that at least one of them prefers their current match over the other. No blocking pairs = stable. Gate: Zero blocking pairs found.

Phase 4: Output

Return matching with stability confirmation.

Output Format

{
  "matching": [{"proposer": "Candidate_A", "reviewer": "Company_X", "proposer_rank": 1, "reviewer_rank": 2}],
  "metadata": {"pairs": 10, "rounds": 23, "blocking_pairs": 0, "proposer_side": "candidates"}
}

Read the full file on GitHub · 86 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 12d ago First seen · 86 lines · 68 tokens per session scan A a2aed3a9fb45

Subscribe to this mod's changes

"algo-hr-matching" is a skill published in the GitHub repository charlieviettq/awesome-agent-skill (25 stars, last pushed 1mo ago), licensed MIT. It adds 68 tokens to every session and 876 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to algo-hr-matching, differing in 8 lines, and is treated as a copy.

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