feedback-query

feedback-query is a skill for Claude Code from leopu00/job-hunter-team. It costs 90 tokens per session (2,139 once invoked), scanned A, original, MIT.

A way to read a user’s reactions to job postings from cloud storage, either one posting at a time or across a period. Reactions include likes, dislikes, hiding, starring, and cleared judgements.

In plain words
What is it for?
Helping scoring, mentoring, and job-search agents learn from feedback, count recurring patterns, and use earlier reactions when evaluating new positions.
Why use it?
Past reactions provide evidence about the user’s preferences for future job recommendations. It also keeps private machine-generated reasons separate from text that may be shown to the user.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is python3 /app/shared/skills/feedback_query.py check <legacy_id>.

Good fit Helping scoring, mentoring, and job-search agents learn from feedback, count recurring patterns, and use earlier reactions when evaluating new positions.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/leopu00/job-hunter-team
agentmods
npx agentmods add skills/leopu00/job-hunter-team/feedback-query

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 feedback-query

README.md
[![agentmods](https://agentmods.dev/badge/skills/leopu00/job-hunter-team/feedback-query/github.svg)](https://agentmods.dev/skills/leopu00/job-hunter-team/feedback-query)
Your own site
<a href="https://agentmods.dev/skills/leopu00/job-hunter-team/feedback-query"><img src="https://agentmods.dev/badge/skills/leopu00/job-hunter-team/feedback-query/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 feedback-query

Your own site · 80×15
<a href="https://agentmods.dev/skills/leopu00/job-hunter-team/feedback-query"><img src="https://agentmods.dev/badge/skills/leopu00/job-hunter-team/feedback-query.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 90 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,139 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00090 $0.02139
Opus 5 $0.00045 $0.01069
Sonnet 5 $0.00018 $0.00428
Haiku 4.5 $0.00009 $0.00214

Measured 11d ago against content hash 1decd75b633c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

feedback-query 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 11d 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.

agents/_skills/feedback-query/SKILL.md · 128 lines

How it starts

The opening of the file, as written. The whole thing — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Raw/display boundary (RAW_DISPLAY_BOUNDARY)

reason and comment are raw machine input. Never quote, relay, summarize, or expose them to the user. Any user-facing note or message must use only display_reason / display_comment; theme label / examples have already crossed the same shared sanitizer. A note is only a closed no-signal:* enum: treat it as availability state and never turn it into infrastructure detail.

feedback-query — User feedback per position

The user can click like/dislike/hide/star on any position from the web dashboard. Those clicks are stored in Supabase position_feedback (mig 019 base + mig 028 extended) and surfaced to agents via this skill. Schema:

Column Type Meaning
position_legacy_id TEXT The legacy_id (string) of the position in positions
action TEXT One of like, dislike, hide, star, clear (mig 059 — the user withdraws the judgement; the latest event wins, so a trailing clear means "no judgement")
reason TEXT Optional short reason (≤500 char)
comment TEXT Optional verbose comment (≤2000 char, mig 028)
score INTEGER Optional 1-5 granular score (mig 028)
direction TEXT Optional more_like_this / less_like_this — pattern signal for the Scout, NOT per-position skip (mig 028)
created_at TS Submission time

The skill calls GET /api/positions/{legacy_id}/feedback on the cloud (using the bearer token in $JHT_HOME/cloud.json). On cloud-disabled or network failure, the skill does not error — it returns ok=true, latest_action=null with a note field. Agents must keep going.

Single position lookup

python3 /app/shared/skills/feedback_query.py check <legacy_id>

Output (JSON on stdout):

{
  "ok": true,
  "legacy_id": "42",
  "latest_action": "dislike",
  "latest_direction": "less_like_this",
  "count": 2,
  "actions": [
    {"action": "dislike", "created_at": "2026-05-30T14:21:00Z",
     "reason": "too senior", "comment": "5+ anni in Java richiesti, non mi interessa stack legacy",
     "display_reason": "too senior", "display_comment": "5+ anni in Java richiesti, non mi interessa stack legacy",
     "score": 2, "direction": "less_like_this"},
    {"action": "like", "created_at": "2026-05-28T09:00:00Z",
     "reason": null, "comment": null, "display_reason": null,
     "display_comment": null, "score": null, "direction": null}
  ]
}

Read the full file on GitHub · 128 lines

Files

What ships with it

6 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. 11d ago First seen · 128 lines · 90 tokens per session scan A 1decd75b633c

Subscribe to this mod's changes

feedback-query is a skill published in the GitHub repository leopu00/job-hunter-team (49 stars, last pushed 3d ago), licensed MIT. It adds 90 tokens to every session and 2,139 once invoked, about $0.0005 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 2026-08-30.