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Found 47 Skills
Internal sub-skill: agentic review of a printed CLI's sampled command output for plausibility issues that rule-based checks can't encode (substring-match relevance, format bugs, silent source drops, ranking failures). Invoked via the Skill tool by main printing-press SKILL.md (Phase 4.85) and printing-press-polish SKILL.md during the diagnostic loop. Not for direct user invocation — its actionable wrappers are /printing-press and /printing-press-polish.
Encode and decode Swift types to and from JSON, property lists, and other external representations using Codable, JSONEncoder, and JSONDecoder. Use when implementing API response parsing, custom CodingKeys for key remapping, custom init(from:) or encode(to:) for complex transformations, nested or flattened JSON structures, heterogeneous array decoding, date and data decoding strategies, lossy array wrappers, Codable integration with URLSession, SwiftData, or UserDefaults, or when configuring encoder/decoder output formatting and key strategies.
Render JSON artifacts into readable UI with an inspect-first, facts-first workflow. Use when Codex needs to turn JSON files, JSON-producing shell commands, CLI output artifacts, or unknown structured payloads into a declarative UI spec that can be rendered natively by the harness or through a terminal-native reference renderer, including cases with repeated child records encoded as aligned arrays.
Audit a test suite to find tests that give false confidence — tests that encode bugs, duplicate coverage, or are so heavily mocked they can't catch real regressions. Use to improve robustness, audit coverage, or harden a risky area.
Identify undefined areas in the current feature specification by asking up to 5 highly targeted clarification questions, and encode the answers back into the specification. Trigger words include: "speckit-clarify", "speckit clarification", "specification clarification", "feature clarification", "identify ambiguities", "clarify requirements".
Classical cipher analysis playbook. Use when encountering substitution ciphers, Vigenere, transposition, XOR, or encoded text in CTF challenges that requires frequency analysis, Kasiski examination, or known-plaintext cryptanalysis.
Deep persona design for Agentforce agents with 50-point scoring. TRIGGER when: user designs agent personas, defines agent personality/identity, creates persona documents, encodes persona into Agent Builder fields, or asks about agent tone/voice/register. DO NOT TRIGGER when: building agent metadata (use sf-ai-agentforce), testing agents (use sf-ai-agentforce-testing), or Agent Script DSL (use sf-ai-agentscript).
Implement Swift Codable models for JSON and property-list encoding and decoding with JSONDecoder, JSONEncoder, CodingKeys, and custom init(from:) or encode(to:). Use when parsing API responses, remapping keys, flattening nested JSON, handling date or data decoding strategies, decoding heterogeneous arrays, or integrating Codable with URLSession, SwiftData, or UserDefaults.
Interact with ServiceNow instances via the jsn CLI. Use when working with ServiceNow development, administration, or data exploration. Handles tables, records, business rules, flows, script includes, ACLs, update sets, and more. Triggered by ServiceNow URLs (service-now.com, servicenow.com) or when the user mentions ServiceNow, jsn, servicenow, or related terms like tables, records, business rules, flows, script includes, ACLs, update sets, or encoded queries.
PointPillars for 3D object detection from LiDAR point clouds. Encodes point clouds into a pseudo-image via a pillar-based representation, then applies 2D detection — used in autonomous driving and robotics. Use when training, evaluating, exporting, pruning, retraining, or running inference for a TAO PointPillars model. Trigger phrases include "train PointPillars", "LiDAR 3D detection", "point-cloud object detection", "pillar-based 3D detector".
Data validation patterns including schema validation, input sanitization, output encoding, and type coercion. Use when implementing validate, validation, schema, form validation, API validation, JSON Schema, Zod, Pydantic, Joi, Yup, sanitize, sanitization, XSS prevention, injection prevention, escape, encode, whitelist, constraint checking, invariant validation, data pipeline validation, ML feature validation, or custom validators.
Extracts hidden or encoded text from GCODE files by analyzing toolpath geometry and coordinate data. This skill should be used when tasks involve decoding text from 3D printing files, recovering embossed or engraved text from GCODE, or CTF-style challenges involving GCODE analysis. Applies to any task requiring geometric reconstruction of text from CNC or 3D printer movement commands.