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recruiting-funnel-analytics

recruiting-funnel-analytics is a skill for Claude Code from trycomp-io/comp-skills. It costs 236 tokens per session (1,608 once invoked), scanned A, original, MIT.

A recruiting pipeline analysis tool for candidate data stored in a CSV file. A CSV is a spreadsheet-like file where each row can represent one candidate and their progress through hiring stages.

In plain words
What is it for?
Use it to calculate stage-by-stage conversion, time to hire or time in each stage, offer acceptance rates, rejection reasons, and results by candidate source.
Why use it?
It shows where candidates drop out and which parts of the hiring process are working or slowing down. This makes it easier to compare sources and identify hiring bottlenecks.

Skill for Claude Code

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

Part of the comp-skills plugin — 37 skills shipped together

not rated 2repo 3mo ago A scan 236 tokens original MIT

Good fit Use it to calculate stage-by-stage conversion, time to hire or time in each stage, offer acceptance rates, rejection reasons, and results by candidate source.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/trycomp-io/comp-skills/recruiting-funnel-analytics
View source ↗ trycomp-io/comp-skills
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 trycomp-io/comp-skills --skill recruiting-funnel-analytics
Clone the repo
git clone --depth 1 https://github.com/trycomp-io/comp-skills

Made for: Claude Code.

Or install comp-skills, the plugin that ships this one along with the rest of its 37 skills.

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 recruiting-funnel-analytics

README.md
[![agentmods](https://agentmods.dev/badge/skills/trycomp-io/comp-skills/recruiting-funnel-analytics.svg)](https://agentmods.dev/skills/trycomp-io/comp-skills/recruiting-funnel-analytics)
Your own site
<a href="https://agentmods.dev/skills/trycomp-io/comp-skills/recruiting-funnel-analytics"><img src="https://agentmods.dev/badge/skills/trycomp-io/comp-skills/recruiting-funnel-analytics.svg" alt="Measured on agentmods" height="20"></a>
Per session 236 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,608 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 $0.00236 $0.01608
Opus 5 $0.00118 $0.00804
Sonnet 5 $0.00047 $0.00322
Haiku 4.5 $0.00024 $0.00161

Measured 8d ago against content hash 349a7ba384b8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

recruiting-funnel-analytics 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 8d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (eam_client.py, scripts/recruiting_funnel.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/recruiting-funnel-analytics/SKILL.md · 117 lines

How it starts

The opening of the file, as written. The whole thing — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Dual-mode operation (Code + Cowork)

HTML through the design system (required). Whenever this skill produces HTML, load the comp-html-guidelines skill first and apply the CompDS design system. This holds even when the user does not ask to "style it" or "make it look good" — every HTML output from this skill goes through the design system. It does not change the methodology below; it only governs the HTML's visual layer.

Detect platform at start:

  • If you have the Bash tool AND can run Python → use script mode (deterministic, writes the rich HTML report). This is the existing workflow below.
  • Otherwise (e.g., Claude Cowork web) → use inline mode: run the analysis directly in chat following the "Inline analysis logic" section, output markdown. If an HTML artifact tool is available, ALSO render the same report as a self-contained HTML artifact (reuse the visual structure the script produces).

Both modes apply the same methodology.

Inline analysis logic (Cowork mode)

Como o usuário fornece os dados

  • Um CSV de pipeline, uma linha por candidato. Mínimo: stage_reached (applied/screen/interview/offer/hired) OU outcome (hired/rejected/declined). Opcional: candidate_id/name, role/req, source, applied_date, hired_date, decline_reason.
  • Pipeline grande (>~100 linhas) é difícil de processar manualmente. Sugira rodar em Claude Code (script mode).

Metodologia (fixa, idêntica ao script)

  1. Estágio mais avançado por candidato: mapeie stage_reached pra um índice no funil canônico applied(0)→screen(1)→interview(2)→offer(3)→hired(4). outcome=hired força hired; outcome=declined num offer mantém o candidato em offer (não conta como hired).
  2. "Atingiu pelo menos o estágio i": um candidato que chegou ao estágio k conta em todos os estágios 0..k.
  3. Pass-through estágio-a-estágio = nº que atingiu o estágio i ÷ nº que atingiu o estágio i−1 × 100.
  4. Gargalo = estágio (de screen a hired) com o menor pass-through.
  5. Aceite de oferta = contratados ÷ ofertas × 100. Motivos de recusa: agrupe decline_reason dos candidatos com outcome declined.
  6. Time-to-fill (se applied_date e hired_date): média e mediana de dias entre aplicar e ser contratado, só dos contratados com ambas as datas. Aceita formatos YYYY-MM-DD, DD/MM/YYYY, etc.
  7. Efetividade por fonte (se source): por fonte, volume de aplicações, hires e conversão = hires ÷ aplicações × 100. Ordene por hires e conversão.

Read the full file on GitHub · 117 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. 8d ago First seen · 117 lines · 236 tokens per session scan A 349a7ba384b8

Subscribe to this mod's changes

recruiting-funnel-analytics is a skill published in the GitHub repository trycomp-io/comp-skills (2 stars, last pushed 3mo ago), licensed MIT. It adds 236 tokens to every session and 1,608 once invoked, about $0.0012 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.

Analytics and metricsDocumentsSpreadsheetsbrazilclaudeclaude-skillscompensationhrpeople-analytics
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