Categories › Productivity & Office › Project & task management
Deterministic digital jobs with independently verified deliverables.
Remote server: your requests and data go to swishrjobs.com. Claude Code: claude mcp add --transport http swishrjobs https://swishrjobs.com/mcp · Claude app: Settings → Connectors → Add custom connector.
The tools this server listed when we connected to it, in its own words.
list_capabilities — List every task SwishrJobs can execute, with each one's inputs, deliverables, price, and whether it can run right now.get_performance — Return the measured success rate, latency, and expected cost per accepted result for each capability, from controlled synthetic benchmarks. select_capability — Rank capabilities for a described task by task match, measured synthetic success rate, and expected cost per accepted result, and explain thpreflight_job — Validate a job request and receive a priced quote without executing anything. Use this to learn the cost and the accepted inputs before authsubmit_job — Authorize and execute a previously quoted job, then return the verified result. Requires explicit authorization. Prefer a capability-specifisubmit_a2a_card_validator — Validate an A2A agent card, report every missing field, and deliver a repaired copy. Before publishing an A2A agent card. Do not choose thissubmit_accessibility_conformance_audit — Audit an HTML page against the WCAG 2.1 success criteria that can be decided from the markup alone — page language, title, headings, a missisubmit_agent_cost_attribution — Attribute agent usage cost across chosen dimensions and rank the groups. When a usage log needs cost attributed to owners or components. Do submit_agent_trace_analyser — Summarise an agent trace: span count, total and slowest duration, and error spans. When a trace has been exported and needs summarising. Do submit_api_contract_diff — Compare two OpenAPI documents and report every breaking change — removed paths and operations, and newly required parameters — with the affesubmit_backtest_overfitting_check — Measure the decay from in-sample to out-of-sample performance and flag parameter-rich strategies. After a backtest, before trusting its in-ssubmit_bank_statement_reconciler — Match a ledger against a bank statement on id and amount, and list every exception. At month-end, when a ledger must be tied to a bank statesubmit_boundary_value_generation — Produce a standard-library Python module that produces boundary values for an integer range, plus pytest tests. Choose this when you need thsubmit_cli_tool_scaffold — Generate a runnable argparse command-line tool with a subcommand per declared name, a test module and a README. At the start of a CLI projecsubmit_commerce_conformance_suite — Check that a service's x402, MCP, A2A and OpenAPI discovery surfaces are all present, well formed and HTTPS-consistent. Before publishing a submit_compliance_evidence_pack — Extract the required contract clauses, map each declared obligation to its supporting sentence, and report the coverage and the gaps. When asubmit_compliance_readiness_pack — Prepare an audit-readiness evidence pack from a project's container, infrastructure, CI and dependency artifacts: run the repository hardenisubmit_cron_expression_check — Validate 5-field cron expressions, name the field that is out of range, and flag the day-of-month and day-of-week combination that most implsubmit_csv_clean — Clean a CSV and return the cleaned file plus a record of every change. Trims cells, makes duplicate and empty column names unique, drops blasubmit_csv_column_profile — Profile every column of a CSV: inferred type (number, integer, date, email or text), non-empty and missing counts, distinct values, and min/submit_csv_date_normalise — Detect date columns in a CSV, report the formats present, flag dates that could be read as day/month or month/day, and return the file with submit_csv_deduplicate — Find duplicate rows in a CSV, group each set with the row numbers it appears on, and return a deduplicated file keeping the first occurrencesubmit_csv_dialect_report — Describe how a CSV is actually shaped: the detected delimiter, the column count, ragged rows with their numbers, duplicate rows, and columnssubmit_csv_json_transformation — Produce a standard-library Python module that transforms CSV text into a JSON array of objects, plus pytest tests. The transformation is chosubmit_csv_missing_value_report — Count how much is missing in each column of a CSV, separating truly blank cells from sentinel values such as NA, null, none, '-', and reportsubmit_csv_preflight — Check a CSV before it is imported. Reports ragged rows, duplicate and empty column names, blank and duplicate rows, per-column type drift ansubmit_csv_quality_report — Score a CSV on completeness, type consistency and uniqueness, per column, and report the columns that are always empty, mostly empty, constasubmit_csv_to_json_rows — Convert a CSV into a JSON array of objects keyed by the header, with documented type coercion: empty becomes null, integers and numbers becosubmit_dashboard_spec_from_questions — Turn a list of business questions into a dashboard specification with a tile and visualisation per question. At dashboard design time, beforsubmit_data_lineage_graph — Derive a table-level lineage graph from a set of create/select statements, with a Mermaid diagram. When a set of SQL models needs a dependensubmit_data_migration_readiness_pack — Profile a source extract against a target schema: per-column type and null profile, unmapped columns, absent target fields, and a go/no-go rsubmit_data_validation_module — Produce a standard-library Python module that validates a record and returns structured errors, plus pytest tests. The rule set is chosen frsubmit_database_migration_review — Review a SQL migration for destructive and blocking operations — dropped tables and columns, NOT NULL columns without defaults, type changessubmit_dataset_quality_report — Produce a standard-library Python module that computes a quality report for an array of records, plus pytest tests. Choose this when you neesubmit_dbt_test_generation — Parse a dbt model's SQL and generate a schema.yml with not_null tests for every selected column. When a dbt model needs baseline tests genersubmit_dependency_vulnerability_triage — Match a lockfile against an advisory feed and return the affected dependencies ranked by severity. When you have a lockfile and an advisory submit_dq_rules_generator — Infer per-column data-quality rules from a sample and generate a test module plus a rules file. When a new dataset needs baseline quality chsubmit_duplicate_group_report — Produce a standard-library Python module that groups records sharing a key field, plus pytest tests. Choose this when you need each repeatedsubmit_edge_case_check — Produce a standard-library Python module that reports boundary conditions for a text value, plus pytest tests. Choose this when a text valuesubmit_embedding_similarity_report — Compare two sets of texts and report the closest match and any near-duplicates. When deduplicating or matching records by text similarity. DNot tested by KitScout yet. When our harness runs it, pros, cons and the tasks we tried appear here, with the date and evidence.