Claudient

Orchestrate multi-agent teams in Claude Code — set up coordinated sessions with task delegation, inter-agent communication, and parallel execution

Leverage Claude Code's ultra-deep planning mode for complex architecture decisions, multi-file refactors, and system design

Deep code review using Claude Code's thorough analysis mode — security, performance, correctness, and maintainability

Safe isolated testing environment for multi-agent swarm topologies before production deployment

Automatically summarizes the current session context to prevent token window overflow.

Claude Code context pruner: slash command to summarize session and reset token bloat

Produces a campaign performance summary from session-log.md entries. Reports open rates, reply rates, and meeting conversion rates per sequence. Flags top performers (reply rate >10%) and underperformers (reply rate <3%). Recommends one concrete change per underperforming sequence.

Writes a structured CRM activity log entry from a call note, email event, or meeting outcome. Before writing, checks for an existing entry with the same prospect + date + action hash to prevent duplicates. Returns the formatted log entry for the CRM update and appends to session-log.md.

Writes one personalized cold email from a completed account research brief. References a specific trigger from the last 90 days in the first two sentences. Under 120 words. Ends with a low-friction question CTA. Returns the draft for human approval — never sends. Flags banned words before output.

Scores a prospect 0–100 against the AI SDR ICP matrix across 4 dimensions: role seniority, company size, industry fit, and tech stack signals. Returns GO (≥60) / CAUTION (40–59) / NO-GO (<40) with a dimensional breakdown and a one-line decision rationale. Blocks research and outreach for NO-GO prospects unless human overrides.

Writes a meeting confirmation message for a booked discovery call. Includes agenda (3 items), dial-in details placeholder, pre-read link if available, and a 1-sentence prospect context reminder. Personalized to the prospect's trigger and company context. Under 100 words excluding logistics.

Generates a tailored objection response for the four most common SDR objections: price, timing, competitor lock-in, and no-perceived-need. Uses prospect context from the research brief. Under 80 words. Returns draft for human approval before sending.

Classifies an inbound prospect reply by intent: interested / objection / not-now / OOO / referral / unsubscribe / spam. Returns intent label, confidence score (0–100), recommended next action, and a draft response if appropriate. Always surfaces the draft for human approval before sending.

Diagnoses analytics pipeline issues — missing data, metric mismatches, slow queries, failed dbt runs. Traces through data lineage to identify root cause and prescribes fixes.

Audits BI dashboards for accuracy, consistency, and UX. Validates metric calculations, color consistency, drill-down logic, and data freshness. Returns QA report with issues and fixes.

Designs and validates normalized or dimensional data models. Assesses schema design for analytics readiness, identifies grain, cardinality, and fact vs. dimension patterns. Outputs entity-relationship diagram and modeling documentation.

Audits data quality at source and transformation layers. Identifies missing values, duplicates, outliers, referential integrity issues, and freshness gaps. Returns data quality scorecards and remediation steps.

Generates dbt project structure, model scaffolds, and DAG-ready yaml files. Creates staging, mart, and fact/dimension models with proper documentation and testing hooks. Saves as dbt-compliant yaml and SQL files.

Design and analyze A/B tests and experiments — sample size, statistical significance, and result interpretation

Defines business metrics with precision — formula, grain, calculation window, data source, and edge cases. Creates a metrics registry with unambiguous specifications to prevent dashboard drift and calculation mismatches.

Analyzes and optimizes SQL queries for performance, readability, and cost efficiency. Identifies missing indexes, execution plan bottlenecks, and refactoring opportunities. Returns optimized query with before/after metrics.

Generate comprehensive API test suites — contract tests, integration tests, and load tests from OpenAPI specs

Design secure authentication and authorization flows — OAuth2, JWT, API keys, and RBAC for APIs

Design consistent, actionable error response schemas with proper HTTP status codes and error categorization

Generate comprehensive OpenAPI 3.1 specifications from API design requirements and existing endpoints

Design rate limiting and throttling strategies for APIs with proper headers, quotas, and backpressure handling

Generate typed client SDKs from OpenAPI specifications for TypeScript, Python, Go, and other languages

Design API versioning strategies — URL path, header, or query parameter versioning with deprecation planning

Design and implement webhook systems with payload signing, retry logic, and delivery monitoring

Profiles a B2B company across 5 dimensions: financial position, organizational structure, technology stack, competitive landscape, and stated pain points. Produces a 1–2 page diagnostic summary with firmographic data, org chart sketch, tech inventory, competitor positioning, and prioritized pain points.

Creates commercial term sheet for B2B consulting engagement, M&A transaction, partnership, or investment. Covers pricing model, payment schedule, SLAs, warranties, termination, and contingencies. Output: 2–3 page term sheet with executive summary, key terms, risk allocation, and legal handoff instructions.

Auto-logs consulting engagement activity, recommendations delivered, client feedback, and outcomes to session-log.md. Triggered after each deliverable or client interaction. Maintains structured record of all advisory work for follow-up, billing verification, and case study documentation.

Identifies 5–7 high-impact opportunities for a B2B client using MECE (Mutually Exclusive, Collectively Exhaustive) analysis across business functions, customer segments, and revenue levers. Ranks each opportunity by impact vs. implementation effort with 2-3 sentence rationale. Output: 1–2 page opportunity list with ROI estimates and success metrics.

Identifies, rates, and mitigates key execution risks for strategic recommendations, organizational changes, or deal structures. Produces risk register with impact/probability matrix, mitigation strategies, contingency triggers, and escalation paths. Output: 1–2 page risk assessment document with prioritized risk list and response plan.

Designs a 90-day strategic roadmap with 3 phases (Foundation / Build / Scale), milestone deadlines, resource requirements, success metrics, and dependency mapping. Output: 3–5 page strategic roadmap document with phase details, executive summary, risk flags, and monthly checkpoint calendar.

Designs and documents bioinformatics analysis pipelines for genomics, transcriptomics, and proteomics data. Outputs reproducible pipeline definitions with tool versions, parameters, and quality control checkpoints.

Designs rigorous biological experiment protocols with power analysis, control strategy, randomization plan, and step-by-step methodology. Outputs a structured protocol document with exact reagent concentrations, timing, and sample size justification.

Drafts NIH/NSF-style grant proposals with structured Specific Aims, Research Strategy, and budget justification. Follows agency-specific formatting requirements and review criteria alignment.

Creates structured electronic lab notebook entries with complete experimental records including materials, conditions, observations, deviations, and raw data references. Entries follow FAIR data principles.

Performs systematic literature reviews with structured search strategies, inclusion/exclusion criteria, and evidence synthesis. Outputs a PRISMA-style summary with evidence quality assessment and gap analysis.