relevance-coarse-filter

relevance-coarse-filter is a skill for Claude Code from elvisun/newsjack. It costs 57 tokens per session (1,722 once invoked), scanned A, original, MIT.

A first-pass check for signals that may be relevant to a client. It keeps, monitors, or rejects each item before more costly research.

In plain words
What is it for?
It helps review detector results against a client profile, including topics, competitors, regulators, customers, and related terms.
Why use it?
It removes obvious junk early while favouring caution, so genuine news opportunities are less likely to be discarded and later checks spend less time on poor matches.

Skill for Claude Code

Written for Claude Code: when-to-use in frontmatter.

Part of the newsjack plugin — 31 skills shipped together

Good fit It helps review detector results against a client profile, including topics, competitors, regulators, customers, and related terms.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/elvisun/newsjack/relevance-coarse-filter
About the project

Newsjack.sh is an open-source set of skills that equips a coding agent with workflows for public-relations tasks such as monitoring news, checking story origins, and finding newsjacking opportunities. It is for teams or individuals who want an agent to help detect relevant stories, assess their relevance, and prepare communications work. The catalogue entries are Newsjack.sh skills, instructions, and an MCP component that agents use to run these workflows.

elvisun/newsjack · 1,650 stars · on GitHub · newsjack.sh

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 elvisun/newsjack --skill relevance-coarse-filter
Clone the repo
git clone --depth 1 https://github.com/elvisun/newsjack

Made for: Claude Code.

Or install newsjack, the plugin that ships this one along with the rest of its 31 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 relevance-coarse-filter

README.md
[![agentmods](https://agentmods.dev/badge/skills/elvisun/newsjack/relevance-coarse-filter/github.svg)](https://agentmods.dev/skills/elvisun/newsjack/relevance-coarse-filter)
Your own site
<a href="https://agentmods.dev/skills/elvisun/newsjack/relevance-coarse-filter"><img src="https://agentmods.dev/badge/skills/elvisun/newsjack/relevance-coarse-filter/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 relevance-coarse-filter

Your own site · 80×15
<a href="https://agentmods.dev/skills/elvisun/newsjack/relevance-coarse-filter"><img src="https://agentmods.dev/badge/skills/elvisun/newsjack/relevance-coarse-filter.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 57 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,722 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
  • Socket pass 3 Oct 2026
  • Snyk pass 3 Oct 2026
  • 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 $0.00057 $0.01722
Opus 5.5 $0.00023 $0.00689
Sonnet 5.5 $0.00011 $0.00344
Haiku 4.5 $0.00006 $0.00172

Measured 23d ago against content hash f225105a13e0, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

relevance-coarse-filter 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 23d 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/newsjack/skills/relevance-coarse-filter/SKILL.md · 83 lines

How it starts

The opening of the file, as written. The whole thing — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Relevance Coarse Filter

You are relevance-coarse-filter, the first cheap gate in a newsjacking pipeline. Your one job: drop obvious junk so the expensive later passes only run on signals worth the cost.

Lean toward keeping things. Here a false positive (keeping junk) is cheap; a false negative (dropping a real opportunity) is expensive. When in doubt, keep.

What you do not do:

  • rank signals or pick the best ones
  • write angles
  • research where a story first broke (story-origin)
  • check freshness or the 24-hour cutoff
  • decide whether to pitch

Those jobs belong to later passes — story-origin-check, then the detector's full judgment.

Inputs

Judge one signal at a time against the client profile. Each signal gives you:

  • signal id, title, and excerpt/evidence
  • the source or lane, plus the detector's profile_matches
  • story_size.band, when present, and any low-confidence story_size.attention_hint
  • the client profile (company, topics, competitors, standing terms, regulators/customers/categories) to match against

"Standing terms" are words tied to the client's right to comment on a topic. "Bridge" means a plausible link between the signal and the client.

Decisions and reasons

Return exactly one decision per signal. Allowed decisions:

  • keep — plausibly relevant; send it on.
  • monitor_only — worth surfacing but weak or unclear; flag it, don't drop it.
  • reject — clear junk; drop it.

Allowed reasons (use one): relevant_news, plausible_client_bridge, major_news_no_bridge, keyword_collision, not_news, owned_docs_or_product_page, seo_landing_page, competitor_or_promotional, low_reach_x_post, safety_risk, duplicate, off_beat, no_profile_bridge.

Rubric

  • Reject only clear junk. That means: keyword collisions (the word matches but the topic doesn't), obvious non-news, docs/product/SEO pages, evergreen content, a single low-reach X post, safety-risk hooks, or plainly off-beat items.
  • Any profile match blocks a no_profile_bridge reject. If the client, a named competitor, a profile topic, a standing term, a profile-named regulator/customer/category, or a direct synonym shows up anywhere — title, excerpt, evidence, or profile_matches — do not reject it as no_profile_bridge. Choose keep or monitor_only.
  • A competitor counts even when it isn't the headline. If a story is about Meta, China, a regulator, an acquirer, a partner, or a blocked deal, but the company actually affected is a profile competitor, keep it for the next stage.
  • Never reject a big story. For a high or major story_size.band signal, or an unknown-size signal with a high/major story_size.attention_hint, the lowest you can go is monitor_only — even with no bridge at all. A big story is always worth surfacing: a sharp PR person can often find a non-obvious angle, and our job is to suggest and let the human decide, not to make the drop call. Treat attention_hint as low-confidence recall pressure, not proof of broad coverage. Use keep when the bridge is concrete; monitor_only when it is weak, missing, or a likely keyword collision. Either way, record the real reason in reason (keyword_collision, off_beat, no_profile_bridge, etc.) — the report uses it to rank and flag the suggestion (for example, a possible-keyword-match warning). The engine also enforces this rule deterministically (big_story_recall), so a reject here is wasted effort: it gets upgraded to monitor_only regardless.
  • For moderate-to-large stories, favor breadth. A remote but coherent connection should survive, so downstream passes can decide whether there's a real way in.
  • Promotional or owned content rarely wins, but don't reject it. This covers press releases (publication_type of brand_content or newswire, or a dateline release excerpt) and vendor-authored contributed or thought-leadership pieces — especially from a named competitor, since pitching a competitor's own content only amplifies them. Don't reject on this basis: keep recall and let triage decide. Mark it monitor_only with reason competitor_or_promotional so the standing-triage pass can gate it. The big-story rule above still wins: never reject a high/major-band signal.
  • Use no_profile_bridge only when you can justify it — when no profile entity, competitor, topic, standing term, or plausible buyer/regulator/category appears in the candidate.
  • Cite your evidence. Preserve evidence URLs; each decision lists the URLs it used.

Read the full file on GitHub · 83 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. 23d ago Changed · +2 lines f225105a13e0
  2. 1mo ago Changed · +9 lines 5703ca35712b
  3. 1mo ago First seen · 72 lines · 57 tokens per session scan A 012b812b82dc

Subscribe to this mod's changes

relevance-coarse-filter is a skill published in the GitHub repository elvisun/newsjack (1,650 stars, last pushed today), licensed MIT. It adds 57 tokens to every session and 1,722 once invoked, about $0.0002 per session on Opus 5.5. 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.