social-intel

social-intel is a skill for Claude Code, Codex from SELAT-AI/selat-skills. It costs 114 tokens per session (1,259 once invoked), scanned A, original, Apache-2.0.

A web-research tool that combines results from two independent search services into a cited brief about a topic, brand, or product. It compares the sources and marks claims that appear in only one of them.

In plain words
What is it for?
Use it to investigate what people are saying about a company, product, brand, or topic, including trends and broader web context.
Why use it?
It reduces dependence on a single search provider and makes it easier to separate corroborated information from isolated claims. The result includes sources so findings can be checked.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: positional $N argument.

Good fit Use it to investigate what people are saying about a company, product, brand, or topic, including trends and broader web context.

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Install with agentmods
npx agentmods add skills/selat-ai/selat-skills/social-intel
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 SELAT-AI/selat-skills --skill social-intel
Clone the repo
git clone --depth 1 https://github.com/SELAT-AI/selat-skills

Made for: Claude Code, Codex.

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 social-intel

README.md
[![agentmods](https://agentmods.dev/badge/skills/selat-ai/selat-skills/social-intel/github.svg)](https://agentmods.dev/skills/selat-ai/selat-skills/social-intel)
Your own site
<a href="https://agentmods.dev/skills/selat-ai/selat-skills/social-intel"><img src="https://agentmods.dev/badge/skills/selat-ai/selat-skills/social-intel/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 social-intel

Your own site · 80×15
<a href="https://agentmods.dev/skills/selat-ai/selat-skills/social-intel"><img src="https://agentmods.dev/badge/skills/selat-ai/selat-skills/social-intel.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 114 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,259 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 $0.00114 $0.01259
Opus 5 $0.00057 $0.00629
Sonnet 5 $0.00023 $0.00252
Haiku 4.5 $0.00011 $0.00126

Measured 11d ago against content hash 89aac91ee2e5, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

social-intel 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.

skills/social-intel/SKILL.md · 95 lines

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.

social-intel

Grounded web-context intelligence on any topic, brand, or account. The skill runs two independent web searches — Exa (neural, MPP on Tempo) and Tavily (advanced, x402 on Base) via the SELAT Router (x402) — and the agent fuses them into a single cited brief, cross-checking the two sources and flagging claims only one of them makes.

When To Use

Use when the user wants a grounded, corroborated web read on a topic, brand, or product — not a single-source lookup. The value is in cross-checking two distinct retrieval methods (Exa's neural/semantic search vs Tavily's aggregation) so the brief is corroborated rather than dependent on one engine. Every API call is a paid x402 service; the agent does the ranking, sentiment read, and synthesis around the paid data.

Rails

Both steps are native x402, via the SELAT Router through the SELAT Router (rail: via the SELAT Router):

  • x402 on Base: Exa web search (api.exa.ai) — resolves as x402 on Base.
  • x402 on Base: Tavily web search (x402.tavily.com) — resolves as x402 on Base.

The selat CLI auto-detects each step's protocol at call time.

Workflow

  1. Install: selat skill install social-intel
  2. Run end-to-end: selat skill run social-intel --topic "<topic>"
  3. The CLI compiles each step into a selat-pay call and prints each result.

Recommended agent procedure:

  1. Ground the topic on the web — Exa POST /search (x402 on Base, ~$0.007); returns ranked results with page text.
  2. Corroborate the web read — Tavily POST /search (x402 on Base, ~$0.011), search_depth: advanced. Cross-reference against Exa; flag claims only one source makes, and prefer sources both engines surface.

Then synthesize: the dominant themes, the strongest sources, and where the two engines agree or diverge — with source URLs.

Inputs And Outputs

Param Required Default Description
topic yes agent payments Keyword/topic to search the web for (both engines).

Read the full file on GitHub · 95 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. 11d ago First seen · 95 lines · 114 tokens per session scan A 89aac91ee2e5

Subscribe to this mod's changes

social-intel is a skill published in the GitHub repository SELAT-AI/selat-skills (2 stars, last pushed today), licensed Apache-2.0. It adds 114 tokens to every session and 1,259 once invoked, about $0.0006 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.

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