Borrowing it
Nothing to install: this file belongs to conectlens/lenserfight. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/conectlens/lenserfight/main/.claude/agents/lenserfight-profile-access-team/05-feed-ranking-relationship-engineer/SKILL.mdgit clone --depth 1 https://github.com/conectlens/lenserfightWrote 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.
[](https://agentmods.dev/skills/conectlens/lenserfight/05-feed-ranking-relationship-engineer)<a href="https://agentmods.dev/skills/conectlens/lenserfight/05-feed-ranking-relationship-engineer"><img src="https://agentmods.dev/badge/skills/conectlens/lenserfight/05-feed-ranking-relationship-engineer/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.
<a href="https://agentmods.dev/skills/conectlens/lenserfight/05-feed-ranking-relationship-engineer"><img src="https://agentmods.dev/badge/skills/conectlens/lenserfight/05-feed-ranking-relationship-engineer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00037 | $0.00552 |
| Opus 5 | $0.00018 | $0.00276 |
| Sonnet 5 | $0.00007 | $0.00110 |
| Haiku 4.5 | $0.00004 | $0.00055 |
Grade A, and why
social-ranking-relationship-engineer 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.
How it starts
The opening of the file, as written. The whole thing — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feed Ranking + Relationship Engineer
Mission
Upgrade LenserFight's social graph beyond a bare follower system.
Principle
Do not copy Instagram/X ranking blindly. Extract the primitives that matter:
- explicit follow edges
- reciprocal follow strength
- interaction intensity
- freshness
- creator quality / trust
- viewer eligibility under privacy policy
Ranking primitives
Graph signals
- viewer follows author
- author follows viewer
- mutual follow
- accepted follow age
- recent profile visits
- recent replies/comments/votes
- repeated prompt execution interactions
- shared communities / shared battles
Content signals
- recency
- engagement velocity
- completion rate
- save/reuse/remix rate
- battle win rate / trust score
- moderation risk penalties
Visibility gates
Before ranking anything, check eligibility:
- author account must be
active - if author is private, viewer must be owner or approved follower for full private content
- restricted-shell eligible viewers may discover profile identity, not gated content bodies
- deactivated / pending_deletion / deleted authors are excluded
Minimum algorithm v1
Feed candidate generation
- accepted follows
- mutual follows boost
- second-degree neighbors with shared communities
- popular public content fallback
Scoring formula example
score = recency_weight + relationship_weight + interaction_weight + quality_weight - risk_penalty
Where:
relationship_weightis highest for mutual follows and accepted follows- private content gets no ranking attempt for unauthorized viewers
Private account discovery rules
Recommended:
- active private accounts may appear in people search and suggested follows
- private content does not appear in public feed bodies
- follower count and trust markers can still power follow conversion
Friendship interpretation
Implement friendship as tiers:
- Tier 0: no edge
- Tier 1: pending request
- Tier 2: accepted one-way follow
- Tier 3: mutual follow (friend)
- Tier 4: trusted circle / close circle later
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.
- 12d ago First seen · 95 lines · 37 tokens per session scan A 1972868fcba5
social-ranking-relationship-engineer is a skill published in the GitHub repository conectlens/lenserfight (18 stars, last pushed yesterday), licensed MIT. It adds 37 tokens to every session and 552 once invoked, about $0.0002 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.
Other skills, from other repositories
potpie-infra-architecture
Use for project infra and architecture context: environments, adapters, runtime configuration, deployments, service dependencies, datastores, API contracts, ownership, incidents, and dependency blast radius.
potpie-project-preferences
Use before writing, modifying, reviewing, refactoring, or testing code so repo/project preferences surface: error handling, file structure, frameworks, logging, dependency choices, testing, security, API style, and naming. Also use after code work when a reusable project preference should be recorded.
api-debugging
Systematic approach to debugging REST APIs, HTTP errors, authentication issues, and network problems. Use when the user has API errors, status code issues, timeout problems, or needs help troubleshooting HTTP requests.
authentication-patterns
OAuth 2.0, JWT, SSO, MFA, NextAuth/Clerk/Supabase Auth implementation patterns.
email-systems
Transactional email (Resend, SendGrid, SES), templates (React Email, MJML), deliverability (SPF/DKIM/DMARC), and inboxing best practices. Use when building email infrastructure, designing templates, or troubleshooting deliverability.
devex-sdk-design
Developer experience (DX) engineering, SDK design patterns, API ergonomics, CLI tooling design, documentation-driven development, and developer onboarding. Use when designing SDKs, improving API ergonomics, building developer tools, or creating developer documentation.