Results for “reputation-scoring”

Rank an existing set of context chunks by relevance, diversity, freshness, and utility. Use when retrieval has already produced candidates that must be scored or reranked; use context-retrieval when the source corpus still needs to be searched.

Load this skill when the user says "resolve comments", "resolve-comments", or "/resolve-comments". Checks open PR review comments, addresses valid ones in a single batched commit, and resolves all threads with appropriate replies.

Prioritize product work with explicit criteria, scoring, tradeoffs, and decision rationale.

Analyzes state merit review for non-covered securities offerings, applying NASAA Statements of Policy to cheap stock, promoter equity investment, voting rights, and promoter compensation. Produces examiner-ready comment responses with cap table analysis and negotiation strategy. Use when filing Reg A, Rule 504, intrastate, or direct public offerings in merit review states, responding to Blue Sky examiner comments, structuring offerings to avoid conditioning, or analyzing NASAA SOPs. Also trigger on cheap stock analysis, promoter equity tests, unequal voting rights review, state examiner correspondence, or phrases like "merit review issues" or "the state examiner sent comments."

Multi-dimensional lead qualification scoring. Evaluates leads against BANT criteria, firmographic fit, behavioral signals, and intent indicators. Outputs qualified/disqualified verdict with detailed reasoning.

Decide which pull-request review comments are actionable. Use when addressing review feedback, monitoring a PR, or filtering already-handled comments.

Improve existing content and close the learning loop without cannibalizing new-content work.

Use to compare BPO sites, vendors or partner teams fairly, adjusting for the work mix each is given before concluding anything about performance. Trigger for "compare our BPO sites", "which vendor is performing best", "site A scores lower than site B", outsourcer QBR packs, partner MI reporting, or setting contractual quality targets with a vendor.

Classify reply sentiment and determine next action

Naming Craft

Score raw leads as HOT/WARM/COOL based on config-driven weights from agency.config.json

Score Analyzer

Deterministically score, route, rank, and select at most one fully vetted Pleasur.ai Stage 01 blog-keyword candidate using product-fit-dominant business value, traffic opportunity, brand fit, DR-relative winnability, and a free-seeker penalty. Use only after BID and AIO evaluation are complete.

Monitor social platforms and forums for brand mentions, category discussions, and competitor activity

Turn "is this account a real fit?" into a stacked verdict. A composite 0-100 fit score built from every signal you have, a breakdown by source, override flags for when a scoring tool is wrong, a channel classification, and a written rationale. Built for reps, marketers, and RevOps, customizable to your CRM and whatever scoring you use. Trigger on "is {account} a real fit?", "score this list against our profile", "find lookalikes to our best customers", "why is the score wrong on {account}?", "validate this prospect list", "what's our coverage in {segment}?", or any account or list qualification.

Use when you need to characterize score distributions of a profile HMM on random sequences, such as calibration checks, benchmarking, or filter-behavior experiments.

Build a USASpending relationship snapshot for the incumbent and buying agency on a pursuit row. Use when user needs award flows and rel counts before battlecard or teaming work — deterministic from DuckDB bulk.