Borda
UserA collection of personal AI coding assistant configurations, specialist agents, and automated workflows optimized for Python and ML open-source development.
Categories
Indexed Skills (41)
debug
Investigation-first debugging — gather evidence, form confirmed root-cause hypothesis, hand off to fix mode with diagnosis file. TRIGGER when: user reports a symptom or failing test with Python traceback, or asks to investigate a runtime/CI failure with reproducible evidence; phrases: "debug this failure", "why is X broken", "find the root cause of <error>", "investigate this CI failure". SKIP when: pure config quality issues (use `/foundry:audit`); broad system-wide diagnosis without traceback (use `/foundry:investigate`); user already knows the fix (use `/develop:fix`); non-Python project.
feature
TDD-first feature development — crystallise API as a demo test, drive implementation to pass it, run quality stack and progressive review loop. TRIGGER when: user asks to build new functionality, add a capability, or implement a feature in a Python project; phrases: "add X", "implement Y", "build Z feature", "create a new module for". SKIP when: bug fixes (use `/develop:fix`); refactoring without new behaviour (use `/develop:refactor`); non-Python projects; `.claude/` config changes (use `/foundry:manage`).
fix
Reproduce-first bug resolution — capture bug in failing regression test, apply minimal fix, run quality stack and review loop. TRIGGER when: user reports a bug, regression, or unexpected behaviour in Python code with a traceback, failing test, or issue number; phrases: "fix this bug", "repair X", "broken since Y", "test failing". SKIP when: CI-only failures without local traceback (use `/develop:debug` first); new features (use `/develop:feature`); `.claude/` config issues (use `/foundry:audit`); non-Python projects.
plan
Interactive wizard that scans the codebase, proposes a metric/guard/agent config, and writes a program.md run spec. Also runs cProfile on a file path to surface bottlenecks before prompting for optimization goal.
refactor
Test-first refactoring — audit coverage, add characterization tests, apply changes with safety net, run quality stack and review loop. TRIGGER when: user wants to restructure existing Python code without changing behaviour; phrases: "refactor X", "clean up Y", "extract Z", "restructure this module", "improve code quality". SKIP when: bug fixes (use `/develop:fix`); new features (use `/develop:feature`); mixed refactor+feature — run `/develop:refactor` first, then `/develop:feature`; non-Python projects.
review
Multi-agent code review of GitHub Pull Requests (Python source, documentation (Markdown/RST), and CI/CD config PRs) covering architecture, tests, performance, docs, lint, security, and API design. TRIGGER when: user provides a GitHub PR number (e.g. 42, #42) and asks to review/audit/check it, or provides a saved review-report path with --reply to draft a contributor-facing comment; phrases: 'review PR 123', 'audit this pull request', 'look at PR #42', 'draft a reply for this review report'. SKIP: local file or current git diff review (use /develop:review (requires 'develop' plugin)); non-Python source PRs without Python files (TypeScript-only, Go-only, Rust-only); standalone issue/discussion thread analysis (use /oss:analyse).
brainstorm
Iterative brainstorming skill for turning fuzzy ideas into approved tree documents. Diverges into branches, deepens and prunes them over many rounds, saves a tree doc. Run breakdown on the tree to distill it into a spec via guided questions.
create
Interactive outline co-creation for developer advocacy content — collects format, audience profile, story arc (Problem→Journey→Insight→Action), and voice/tone; detects out-of-scope requests (FAQs, comparison tables); surfaces conflicts between user brief and audience needs. Writes approved outline to .plans/content/<slug>-outline.md for foundry:creator to execute. Use when starting a blog post, Marp slide deck, social thread, talk abstract, or lightning talk.
distill
One-time snapshot extracting patterns from work history and accumulated lessons, distills into concrete improvements — new agent/skill suggestions, memory pruning, consolidating lessons into rules/agent updates, or performing bin/ extraction from /audit --efficiency candidates. Roster boundary analysis → /foundry:audit agents (Check 34).
humanizer
Strip AI-writing tells from prose destined for humans — docs, PR/commit bodies, reports, release notes, blog posts, Slack/email drafts. Removes LLM-vocabulary clichés (delve, boasts, testament, underscore, robust, tapestry...), banned constructions (not just X but Y, rule-of-three triads, "-ing" superficial-analysis clauses, vague-attribution weasel words), and formatting tells (title-case headings, mechanical bolding, em-dash overuse, curly quotes, bare-bullet inline-header lists). TRIGGER when: user asks to humanize/polish/de-AI a piece of text or file; before finalizing a substantial human-facing prose artifact drafted as part of the current task (docs, PR/commit body, report, blog post, release notes, external message) — self-review pass, best-effort model-initiated, not a guaranteed intercept. SKIP when: output is a terse conversational chat reply, code, JSON/YAML/config, a machine-parsed agent envelope ("Return ONLY:"), or the target is an ultra-caveman-tier handover file (`.temp/`, inter-agent prose pe
profile
Session clock-time analyzer. Reads the foundry plugin's timings.jsonl and invocations.jsonl logs (written by task-log.js) and produces a per-session and per-skill wall-time breakdown — local-tool work vs subagent spawns vs Skill invocations vs AskUserQuestion idle vs main-loop reasoning residual. Useful for answering "why did /oss:resolve run 30 minutes?" or "what eats clock time in /develop:fix?". Pure log read — no instrumentation, no skill edits, no LLM calls. TRIGGER when: user asks where wall-clock time goes during a skill/session, why a skill is slow, what dominates total runtime, or wants a per-skill rollup over a recent window; phrases: "where does time go", "why so slow", "profile last session", "clock breakdown", "session timing". SKIP: token/cost questions (model field is null in current logs — out of scope); per-line Python perf (use foundry:perf-optimizer); known failure or hang (use /foundry:investigate).
session
Session parking lot — automatically parks diverging ideas and unanswered questions to project-scoped memory; /session resume shows pending items, /session archive closes them, /session summary gives a session digest TRIGGER when: user asks "what was I working on", "any pending items", "what's in the parking lot", "remind me where we left off", "what did we defer"; resume intent clear from context. SKIP: new topic or explicit new task; user providing new context rather than resuming; archive mode requires user-supplied text (user-initiated only).
setup
Post-install setup for foundry plugin. Run once after installing on a new machine, or after a plugin version upgrade to sync settings and symlinks. Merges statusLine, permissions.allow, enabledPlugins, and advisorModel into ~/.claude/settings.json; symlinks rules, TEAM_PROTOCOL.md, and skills into ~/.claude/.
resolve
OSS maintainer fast-close workflow for GitHub PRs. Three phases: (1) PR intelligence — reads full thread, linked issues, PR body to synthesize contribution motivation and classify every comment into action items; (2) conflict resolution — checks out PR branch (fork-aware via gh pr checkout), merges BASE into it, resolves conflicts semantically using contributor's intent as priority lens; (3) implements each action item as separate attributed commit via Codex, pushes back to contributor's fork. Supports three source modes: pr (live GitHub comments only), report (latest /review report findings as action items, no GitHub re-fetch), and pr + report (both sources aggregated and deduplicated in one pass). Also accepts bare comment text for single-comment dispatch. NOT for reply drafting to /oss:analyse findings (use /oss:analyse --reply (requires `oss` plugin)). NOT for code diff review of PR changes (use /oss:review). NOT for release preparation (use /oss:release). NOT for fixing local bugs unrelated to a PR (use
fortify
Systematic ablation study runner. After research:run finds improvements, fortify identifies component candidates from git diff + diary, creates isolated git worktrees per ablation (main repo never modified), runs metric+guard in each worktree, ranks component importance, and optionally generates reviewer Q&A calibrated to a target venue.
judge
Research-supervisor review of program.md — validates experimental methodology (hypothesis clarity, measurement validity, control adequacy, scope, strategy fit), emits APPROVED / NEEDS-REVISION / BLOCKED verdict before expensive run loop.
retro
Post-run retrospective: reads .experiments/ JSONL, computes Wilcoxon significance, detects dead iterations, flags suspicious jumps, generates next-hypothesis queue for --hypothesis flag.
run
Sustained metric-improvement loop with atomic commits, auto-rollback, and experiment logging. Iterates with specialist agents, commits atomically, auto-rolls back on regression. Accepts a program.md file path. Supports --resume, --team, --colab, --codex, --researcher, --architect, --journal, --hypothesis.
sweep
Non-interactive end-to-end pipeline — auto-configure program.md (accept defaults), run judge+refine loop (up to 3 iterations), then run the campaign. Single command from goal to result.
topic
Research State of the Art (SOTA) literature for an Artificial Intelligence / Machine Learning (AI/ML) topic, method, or architecture. Finds relevant papers, builds a comparison table, recommends the best implementation strategy for the current codebase, and optionally produces a phased implementation plan mapped to the codebase. Owns broad SOTA search end-to-end via foundry:web-explorer; delegates codebase mapping to foundry:solution-architect.
verify
Paper-vs-code consistency audit. After research:scientist implements a method from a paper, verify the implementation matches paper claims across five dimensions — formula matching [F], hyperparameter parity [H], eval protocol [E], notation consistency [N], and citation chain [C]. Reads paper (PDF path / arXiv URL / pasted text), maps claims to codebase, emits verification table with match status and severity.
integration
Adapter over `codemap-py integrate` — audit, plan, source-wire, locally sync, and demonstrate the codemap-py integration with its supported consumers. Trigger with `$codemap-py:integration check|plan|apply|sync|demo [--runtime {claude,codex,both}] ...`. Default (no args) is `check`. Skip for: running a structural query (use `$codemap-py:query-code`); explicit standalone index rebuild (use `$codemap-py:scan-codebase`).
query-code
Query the codemap structural index — module deps/rdeps/central/coupled/path, symbol-level source extraction, function call graph (fn-deps, fn-rdeps, fn-central, fn-blast), plus quality/coverage queries. Trigger with `$codemap-py:query-code <subcommand> ...` for: "what depends on", "who calls", "imports of", "dependency graph", "blast radius of", "list central modules". Skip for: rename intent (use `$codemap-py:rename-refs`); simple grep suffices; non-Python repo. Missing/stale index auto-builds — no manual scan-codebase needed.
rename-refs
Atomic rename of Python symbols or modules via the structural index — static callers, import sites, `__all__` re-exports, Sphinx cross-refs; optional deprecated alias (`--deprecate`) or hard-delete (`--remove-if-no-callers`). Trigger with `$codemap-py:rename-refs symbol <old> <new> [flags]` or `$codemap-py:rename-refs module <old_path> <new_path> [--dry-run]` for: "rename X to Y" (function/class/method/ module), "move module X to Y", "update all references to X". Skip for: non-Python; index not built (run `$codemap-py:scan-codebase` first); local-variable rename; grep-only rename wanted; 1:N symbol splits; package directory rename (use `git mv` directly).
scan-codebase
Scan the Python codebase and build a structural JSON index (import graph + blast-radius metrics + symbol table). Explicit invocation only via `$codemap-py:scan-codebase [--root <path>] [--incremental]` — never auto-trigger this from conversation reasoning. Use when the index is missing, stale, or after significant project changes.
test-impact
Identify which tests need rerunning after a code change — traces static call graph (function-level) or import graph (module-level) to find affected test files, then emits a ready-to-run pytest command. Trigger with `$codemap-py:test-impact <module::symbol | module> [--no-mocks]` for: "which tests are affected", "what tests cover this", "test impact of", "what tests to rerun".
audit
Minimal codex-native audit loop. Use to scan codex configuration/workflow drift and emit ranked gaps with measurable gates.
calibrate
Codex-native calibration loop. Use to detect leaks or major gaps across packaged skills and role cards with fixed checks plus behavioral recall, precision, and confidence-accuracy scoring.
investigate
Minimal codex-native investigation loop. Use for unknown failures, code debugging, and root-cause narrowing with measurable gates.
manage
Minimal codex-native management loop. Use to create, update, or remove Codex agents/skills/config entries with guardrails.
analyse
Minimal codex-native analysis loop. Use for issue/PR/problem analysis before implementation with measurable gates.
release
Minimal codex-native release loop. Use for SemVer-aware release readiness with measurable gates and artifact output.
kaggle
Generate or extend grounded Kaggle competition notebooks as Jupytext `# %%` Python scripts. Use for full training notebooks, EDA-only notebooks, checkpoint-based inference notebooks, or resuming an existing Kaggle script across classification, regression, segmentation, detection, tabular, time-series, point-cloud, and mixed-modality tasks.
code-remediate
Codex-native code-remediation loop: triage/apply code-review findings, rerun checks, publish unresolved gaps with measurable gates; `$code-remediate #123 +review` remediates a PR from latest matching code-review artifact.
code-review
Tiered Codex-native multi-axis code review for local diffs or GitHub PRs, including `$code-review
develop
Minimal codex-native develop loop. Use for implementation tasks with linear plan-build-verify flow and measurable quality gates.
optimize
Minimal codex-native optimization loop. Use for metric-driven improvements with guardrails and measurable gates.
research
Minimal codex-native research loop. Use for docs/papers/state-of-the-art scan with source-backed recommendations.
sync
Dry-run-first Codex Rig installation drift and update workflow. Use to inspect the active plugin cache, refresh its GitHub marketplace, or reinstall the current plugin while coordinating separately managed agent shims.
agent-shims
Diagnose, inspect, install, update, or remove the complete Codex Rig user-agent shim roster. Use when the user invokes agent-shims with exactly one action—doctor, status, install, or remove—or asks to manage Codex Rig role agents safely.
debrief-coding
Read local codemap telemetry logs and produce a diagnostic/usage report. Supports date filtering, session filtering, and optional anonymization before sharing. Trigger with `$codemap-py:debrief-coding [--since <YYYY-MM-DD>] [--session <id>] [--anonymize] [--output <path>]` to analyse recent codemap usage, debug query patterns, investigate errors, or prepare a shareable anonymized report of how codemap skills and the CLI are being used.
Bio shown is the top-scored skill's repo description as a fallback — real GitHub bios land in a future update.