llm coding principles
by Roy Yuen
Enforce senior-level coding standards (Surgical, Simple, Goal-Driven) on every AI-generated code change.
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THE AGENSI STORE
118 skills found
by Roy Yuen
Enforce senior-level coding standards (Surgical, Simple, Goal-Driven) on every AI-generated code change.
Audit any AI-generated output for unsupported claims, then verify every factual and technical assertion against its real source before it ships.
A reusable rubric that grades every source by type, recency, authority, independence, and corroboration, then ranks them and resolves conflicts by evidence weight.
Analyzes AI agents for performance, reliability, security, and optimization opportunities.
An adversarial gate that audits a research brief or AI-generated answer for unsupported claims, weak or outdated sources, missing citations, and one-sided framing — returning a structured TRUST/VERIFY/REJECT verdict with the exact passage quoted and what to verify for each.
An adversarial editing gate that scans any AI-assisted draft and flags the exact tells that make it sound machine-written — filler phrases, formulaic structure, robotic cadence, punctuation tics — returning a structured PASS/REVISE/FAIL verdict with specific fixes.
An adversarial senior engineer review gate that audits AI-written code for security gaps and logic errors before shipping.
Continuously monitor data pipelines, detect anomalies, and explain root causes before failures impact production.
Catch typos, homophones, and near-miss misspellings across code, docs, and markdown, in a commit, your staged changes, a file, or a whole directory. Layers dictionary, phonetic (Soundex), and edit-distance checks with context-aware homonym rules to flag the their/there and its/it's a basic spellcheck sails right past.
An adversarial reviewer for AGENTS.md and agent instruction files. It flags ambiguous or contradictory rules, missing guardrails, vague tool and scope definitions, and untestable instructions, then returns a PASS / REVISE / BLOCK verdict — before the config drives your agent.
An adversarial reviewer for landing pages and conversion copy. It flags an unclear value proposition, a weak or buried call to action, missing social proof, funnel friction, and unsupported claims, then returns a PUBLISH / REVISE / HOLD verdict — before the page goes live.
Map supply chains, identify overlooked upstream chokepoints, score candidate quality, audit evidence, and generate research reports.
A pre-publish audit gate to extract claims, verify facts, and flag compliance risks in public-facing content.
Generate a personalized before-you-ship checklist for your app, with the things you already have checked off. Pick your app type (web app, SaaS, store, or content) and it builds a tailored list covering security, legal basics (privacy policy, terms, cookie consent), social preview, payments and refunds, accessibility, analytics, and backups, then scans your repo and pre-checks what is already there. Every item says why it matters in plain English.
An adversarial gate that audits any chart, data summary, or statistic for misleading visuals and unsound inference, then returns one PASS/REVISE/FAIL verdict.
Runs an ordered evidence-integrity gate over any AI draft — grade sources, ground claims, verify technical assertions, stress-test — then returns one PASS/REVISE/FAIL ship decision.
by Lily Studio
Paste your Python code and get a plain-English test report — what works, what doesn't, what's unfinished, and exactly what to do next.
You changed the prompt, tried four inputs, it looked better, you shipped — and three days later support tickets say outputs are worse for an entire class of inputs you didn't test
An adversarial security gate that audits untrusted content — web pages, tool outputs, documents, emails — for embedded instructions, exfiltration, and authority spoofing, then returns a SAFE/REVIEW/BLOCK verdict.
by Joker
Video type matrix, platform specs, AI prompt recipes (Seedance/Sora/Kling), zero-cost SOP, quality gates.
by Shogun Labs
Battle-tested prompting patterns to eliminate LLM output drift. Sandwich structure, few-shot examples, history limits, retry, and token caps — 6 composable layers for production-grade agent reliability.
An adversarial reviewer for job descriptions and candidate-facing hiring content. It flags biased or exclusionary language, risky questions, inflated or vague requirements, and missing disclosures, then returns a POST / REVISE / HOLD verdict. A bias-and-clarity aid, not legal advice.
An adversarial reviewer for AI-written code changes. It pressure-tests a pull request or diff for untested branches, silent behavior changes, missing edge cases, over-confident code that only looks right, and weak tests, then returns a PASS / REVISE / BLOCK verdict before the change merges.
Audit your frontend for accessibility violations before release — flags WCAG failures, gives prioritized fixes, and blocks the broken patterns that get sites sued.