assess

assess is a skill for Claude Code from alwaysmap/jobs4me. It costs 84 tokens per session (1,246 once invoked), scanned A, original, MIT.

A job-posting assessment skill that fetches a role, compares it with a job seeker's profile, and can optionally add it to a tracker.

In plain words
What is it for?
Reviewing job-posting URLs, identifying strengths and gaps against a profile, and optionally saving the assessment and job details.
Why use it?
It helps decide whether a particular role is a good match before spending time applying or recording it.

Skill for Claude Code

Written for Claude Code: ${CLAUDE_PLUGIN_ROOT} variable. Also seen: mentions subagents.

Runs only inside its plugin — its command needs a path that Claude Code sets for a plugin’s own hooks and for nothing else. Install the plugin, not this.

Part of the jfm plugin — 11 skills, 11 commands shipped together

Good fit Reviewing job-posting URLs, identifying strengths and gaps against a profile, and optionally saving the assessment and job details.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.

Claude Code
/plugin marketplace add alwaysmap/jobs4me
Claude Code
/plugin install jfm

Made for: Claude Code.

Or install jfm, the plugin that ships this one along with the rest of its 11 skills, 11 commands.

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 assess

README.md
[![agentmods](https://agentmods.dev/badge/skills/alwaysmap/jobs4me/assess.svg)](https://agentmods.dev/skills/alwaysmap/jobs4me/assess)
Your own site
<a href="https://agentmods.dev/skills/alwaysmap/jobs4me/assess"><img src="https://agentmods.dev/badge/skills/alwaysmap/jobs4me/assess.svg" alt="Measured on agentmods" height="20"></a>
Per session 84 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,246 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 $0.00084 $0.01246
Opus 5 $0.00042 $0.00623
Sonnet 5 $0.00017 $0.00249
Haiku 4.5 $0.00008 $0.00125

Measured 7d ago against content hash 7757de351ca1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

assess 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.

skills/assess/SKILL.md · 91 lines

How it starts

The opening of the file, as written. The whole thing — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Assess a Job Posting

Shell setup: Always export JFM_DIR='<workspace path>' (single quotes) before running tracker commands. The script refuses to operate if it can't resolve a real workspace.

Read ../search/references/routing.md before processing any user message — it defines how to decompose compound messages and where to route each type of input.

Assess a specific job posting against the user's profile.

Steps

  1. Read profile.yaml, archetypes.yaml, and filters.yaml

  2. Fetch the URL provided by the user using WebFetch. Use Haiku for simple JD extraction from URLs if delegating to a sub-agent.

  3. Extract the job description from the page

  4. Run a full fit assessment using the search skill's fit assessment framework

  5. Present the assessment to the user (Recommendation, Gaps, Positive Fit)

  6. Ask if they want to add it to the tracker — or decline it immediately

  7. If adding, add via the tracker script:

    node ${CLAUDE_PLUGIN_ROOT}/scripts/tracker.js add --json '{"company":"...","role":"...","url":"...","archetype":"...","stage":"suggested","agent_summary":"..."}'
    
  8. Get the file paths for the new entry and save the JD:

    Always save the JD locally — Greenhouse / Lever / Ashby postings are removed once roles close, and the user needs the JD for cover letters, prep, and a record of what they applied for. Save the JD even when declining: declined JDs feed the decline-pattern learning loop.

    node ${CLAUDE_PLUGIN_ROOT}/scripts/tracker.js paths --id <id>
    

    This returns role_dir and company_dir. Save the JD to {role_dir}/jd.md. Create the directories if they don't exist (mkdir -p).

    After saving, use present_files to share the board with the user, then tell them what was created:

    Added to tracker — {Company} / {Role} JD saved{role_dir}/jd.md Your board has been updated — refresh to see it.

  9. If declining (user says "not interested", "pass", "decline", etc.):

    • If already added to tracker, decline it:
      node ${CLAUDE_PLUGIN_ROOT}/scripts/tracker.js decline --id <id> --reason "reason text"
      
    • If not yet added, add it as declined so the reason is tracked:
      node ${CLAUDE_PLUGIN_ROOT}/scripts/tracker.js add --json '{"company":"...","role":"...","url":"...","stage":"declined","decision":{"proceed":"no","reason":"reason text"}}'
      
    • Always run decline pattern learning (see ../search/references/decline-learning.md): check if this decline suggests a new pattern or refines an existing one. If so:
      node ${CLAUDE_PLUGIN_ROOT}/scripts/tracker.js add-decline-pattern --pattern "Pattern description" --learned-from "Company Name"
      
      Tell the user what filter change was made (if any). Use present_files to share Kanban/index.html, then tell the user: "Your board has been updated."

Read the full file on GitHub · 91 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 · 91 lines · 84 tokens per session scan A 7757de351ca1

Subscribe to this mod's changes

assess is a skill published in the GitHub repository alwaysmap/jobs4me (2 stars, last pushed 1mo ago), licensed MIT. It adds 84 tokens to every session and 1,246 once invoked, about $0.0004 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.