gmail checker
by Rian O'Leary
A prioritized Gmail digest that filters out promotions and noise to surface urgent and personal emails.
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THE AGENSI STORE
21 skills found
by Rian O'Leary
A prioritized Gmail digest that filters out promotions and noise to surface urgent and personal emails.
by Tate Lyman
Automated launch-readiness auditor for x402 and agent-payment API surfaces.
A professional security triage workflow for mapping attack surfaces and prioritizing DeFi smart contract vulnerabilities.
by LocoLoboZ
Plan, collect, and synthesize lawful defensive intelligence into structured exposure reports and investigation briefs.
Lint a prompt template for the issues that cause injection and flaky output. Flags untrusted variables interpolated straight into the instructions (the injection surface), placeholders that are never provided or never used, contradictory instructions, a missing output-format spec where the result is parsed, unbounded context interpolation, and leftover placeholders. It detects problems; it does not write prompts.
Handle any B2B sales objection with a framework-backed response: classifies it (price, authority, timing, competition, need), then drafts an email or call script tailored to your product and price point, plus the discovery questions that surface the objection behind the objection. Built on LAER, Sandler, and JOLT, not pushy improv.
Surface de-prioritized pharmaceutical assets and "communication cliffs" for investment and licensing opportunities.
Hold your bios, footers, and profiles to one brand spec. Flags brand-name spelling and casing that does not match your canonical form, off-spec taglines, links that are not on your official list, leftover placeholders (Lorem, TODO, "your tagline here"), and handles that differ from one surface to the next. You define the spec once and it enforces it everywhere.
Point it at an unfamiliar or inherited repo and quickly understand it. Maps the architecture, identifies the key modules and entry points, traces the core end-to-end flows, surfaces the conventions and gotchas, and assembles a clean ONBOARDING.md — turning a strange codebase into a clear mental model fast. Built for the moment you join a project, take one over, or have to explain a repo before changing it.
by John Barros
Builds professional, conversion-focused static website surfaces with cinematic design and full SEO metadata.
Apply RICE scoring that surfaces honest numbers instead of advocacy — with calibrated estimates and the reasoning made explicit.
Generate a spec-compliant llms.txt (and optional llms-full.txt) for your site or repo so AI agents and crawlers can navigate it. Curates the pages that matter, writes the exact llmstxt.org structure — single H1, blockquote summary, and link sections in the precise format agents parse — then validates the format and tells you where to put it. The honest version: a low-cost, machine-readable surface for the agentic web, not an overhyped SEO trick.
Audit any page, article, or doc for how likely AI answer engines — ChatGPT, Perplexity, Google AI Overviews, Claude — are to surface and cite it. Checks answer-first extractability, question-shaped structure, quotable units, factual specificity, sourcing, schema, and freshness, then returns a PASS/REVISE verdict with the prioritized fixes. This is Answer Engine Optimization, not classic SEO — it optimizes content to be quoted inside AI answers.
Run this on your plan, spec, or prompt before any work starts. It surfaces the decisions you never made, names what an agent would silently assume for each, ranks them by the cost of a wrong guess, and hands back a short list of choices to make now — plus the gaps that are safe to leave open.
Red-team your own AI agent for prompt-injection and tool-misuse vulnerabilities before it ships — then fix them. Maps your attack surface, generates a defensive test plan with the safe behavior expected for each case, and gives a prioritized mitigations list. Defensive use only.
A defensive catalog of ~39 agent security attack patterns across every surface — injection, tool abuse, exfiltration, memory poisoning, multi-agent trust, retrieval poisoning — each with a detection signal, a concrete defense, and a severity. Nine reference files plus a threat-model worksheet. For hardening agents you own.
Identify ADA Title II web compliance deadlines and audit surfaces against WCAG 2.1 AA for government entities.
Audit release consistency, discovery surfaces, supported claims, evidence freshness, and Product Hunt or Show HN readiness before distributing an agent product.
Surface missing relationship context, mixed register, and unreviewed Japanese business-language patterns.
Reconcile price, availability, and evidence-backed claim meaning across multilingual commerce surfaces.
Reconcile owner-defined AI transparency scope with labels, notices, technical markings, and release claims.