decisionnerd/dev-skills

kiss

Audit goals, processes, systems, and plans for needless complexity — then recommend simplification only when it is warranted.

View source

How to use

  1. Copy the installation command and review the source package before installing it in your own agent environment.
  2. Check the source document for required tools, credentials and supported hosts.
  3. Describe your input and desired deliverable; review the output against the source material.
npx skills add https://github.com/decisionnerd/dev-skills --skill kiss

Before you start

  • Installation does not include a model subscription, API allowance or permission to access your files.
  • Repository stars and installation counts describe activity, not an independent quality or security test.
Original skill document

Rendered from the source repository. Headings, examples, code, tables, links, and referenced images are preserved.

KISS

Keep It Simple — honestly. Look at what is used or planned (goals, processes, systems, workflows), judge whether it is overly complex, and only then recommend simplification. If complexity is earned, say so and protect it.

Simple here means:

  1. A straightforward DAG from now → done (clear dependencies, few parallel critical paths, obvious stop).
  2. Right-sized tasks — not micro-chores that thrash context, not epic blobs that hide risk.
  3. Least mechanism that still serves the vision and constraints (safety, scale, compliance, team reality).

Operating contract

Shared by every DecisionNerd/dev-skills skill. Canonical copy: handbook/concepts/14-operating-contract.md.

  • Define done first. Before using tools, write the finish line in one or two lines: acceptance criteria (existing issue AC, BDD scenarios, tests, or contract; otherwise propose them and where they should live) and the evidence that will prove them. Re-check it before reporting done. Never report done on unverified work.
  • Requested scope sets the finish line. A question ("is it ready?", "why is it broken?", "what next?") ends with the answer and a Next: line naming the exact next invoke. An outcome request ("fix", "finish", "land", "#42") continues through the chain (diagnose → fix → test → check-readiness → merge-it) until the outcome or a real blocker. Do not end a turn with "Do you want me to…?" for in-scope, in-repo work.
  • Stop only for real blockers. Stop and ask only when you cannot continue without the user, or before: deleting data or unmerged work, force-push or history rewrite, changing anything outside this repository (GitHub objects, deployments, live data, production or paid resources, external services), or leaving the requested scope, unless the user's request already named that exact action. Keep the harness's permission prompts for risky commands. Otherwise keep going and put status notes in the same message as the next action.
  • Ask well, once. For a genuine question use the harness's structured question tool when it has one (Claude Code: AskUserQuestion; Codex: request_user_input when the current mode supports it; T3 Code: the question tool) with concrete options; otherwise plain text with numbered options. Treat the answer as settled; do not re-open earlier verdicts, plans, or answers unless asked.
  • Fan out when work is parallel. Use subagents for independent reads (repo survey, evidence gathering, per-option research, per-area audits) and independent verification (a reviewer that did not write the change). Writes stay single-owner per path set and sequential. Brief every child with goal, done-when, constraints, must-not, and return shape; verify each result before consolidating. Use Claude Code's Workflow tool only when orchestrating many subagents truly needs it; it is expensive. T3 Code: its delegated subagents — with optional worktree isolation for independent verification — cover this without the Workflow tool.
  • Pick the model tier per child; defer to routing config. If the harness or user config already routes subagents, follow it and do not pass a model. Otherwise pick a tier per child: mechanical search or inventory → fast/cheap; implementation and evidence gathering → mid; planning, review, adversarial verification → top. Tier names differ per harness (Claude Code: haiku / sonnet / opus or fable; T3 Code: inherit by default or pick from its live provider/model catalog). Set the choice with the harness's spawn model param or agent frontmatter model: (per-harness details: skills/agents/references/sub.md). Where the harness cannot choose, children inherit or the harness picks; say which in the status note.
  • Keep a checklist on long runs. For more than about five steps or work that crosses skills, keep TASKS.md at the repo root and tick items as they finish. Do not commit it unless the repo already tracks one.
  • Close every run with three headings. Blocked on me (the one genuine question or blocker, else "none"); Changed (files, commits, GitHub objects, deploys, else "nothing"); Found (evidence, verdict, and Next: <exact invoke>).

Commands

CommandWhat it does
(none) / auditFull KISS pass on the named (or inferred) target
goalsFocus on goal/scope sprawl vs vision-tied outcomes
processFocus on rituals, checklists, handoffs, approval chains
systemFocus on architecture, services, tools, agent stacks
planFocus on an implementation plan / milestone / issue set
flow / dagDraw or critique the task DAG; resize nodes
help / libraryList commands

Target: path, issue/PR/milestone, doc, plan paste, agent design, or “current work.”

Routing

  1. No args → audit on current git/docs scope (brief survey first).
  2. First word is a command → that lens; remainder is target.
  3. Clear intent (“is this architecture too much?”, “simplify the rollout plan”) → map and run.

Read-only by default. Do not delete systems, rewrite plans, or cut scope until the user accepts a recommendation.

Hard rules

  1. No automatic reductionism. Complexity that buys safety, clarity, scale, or irreversible-risk control can stay. Say keep when keep is right.
  2. Always present benefits and risks of simplifying (and of not simplifying).
  3. Prefer one primary recommendation: simplify / keep / reshape (right-size without net removal).
  4. If recommending simplify, show the simpler DAG and what was removed or merged — and what must remain.
  5. Tasks in the DAG must pass the Goldilocks test: each node is finishable in one focused session (or clearly “part N”), has a done-when, and is not a fake split of a single thought.

Workflow (audit and siblings)

1. Scope the target

Name what you’re kissing: goal set, process, system, plan, or flow. Skim evidence (docs, code layout, issue graph, agent config, user’s paste). If scope is fuzzy, ask one clarifying question (structured question tool when available, else numbered options) or run a 30-second recon-style git glance. For large targets (multiple areas or packages), one subagent per lens/area (fast tier) in parallel; an independent top-tier subagent argues "keep" before you recommend "simplify"; verify each before consolidating.

2. Describe current shape

  • Intent — what success is
  • Pieces — goals / steps / components / roles
  • Coupling — what depends on what (sketch a DAG)
  • Tax — coordination cost, cognitive load, failure modes, time-to-value

3. Complexity verdict

Choose one:

VerdictMeaning
Overly complexMechanism exceeds need; DAG is tangled, tasks wrong-sized, or redundant layers don’t buy required properties
Earned complexityExtra pieces buy real constraints (safety, scale, compliance, multi-team); simplifying would shift risk
Wrong-shapedNot necessarily too much — nodes too big/small, or DAG unclear — reshape without reductionism

Do not invent “overly complex” to have something to cut.

4. Risks & benefits

Always fill both columns:

If we simplify

  • Benefits: …
  • Risks: …

If we keep as-is

  • Benefits: …
  • Risks: …

5. Recommendation

One primary call:

  • Simplify — what to remove/merge/replace; simpler DAG; migration notes
  • Keep — what complexity is doing; what not to touch; optional light cleanup only
  • Reshape — right-size tasks / clarify DAG / rename stages without net capability loss

Optional alternates (≤2). Hand off: refactor-it, issues narrow, milestones narrow, agents design, research-it, idk-now, DocSlime/ProductFeeling if product-shaped.

Output shape

markdown
## KISS: <target>

**Lens:** audit | goals | process | system | plan | flow

**Current shape**
- Intent: …
- Pieces: …
- DAG (sketch): …
- Tax: …

**Verdict:** overly complex | earned complexity | wrong-shaped
**Why:** <3–5 lines>

**Simplify?**
| | Benefits | Risks |
| --- | --- | --- |
| Simplify | … | … |
| Keep as-is | … | … |

**Recommend:** Simplify | Keep | Reshape
**Do next:** <concrete steps or skill invokes>
**Simpler / clearer DAG:** <mermaid or bullets, if recommending change>

**Blocked on me**
(none, or the one genuine question or missing decision)

**Changed**
(nothing — read-only; or what was reworded/removed if reshape was applied)

**Found**
Verdict, recommendation, simpler DAG if applicable. Next: `<exact invoke — e.g. refactor-it, issues narrow, agents design>`.

Goldilocks task sizing

Too smallJust rightOverly big
Split that forces thrash / fake progressOne session, clear done-when, single ownerHides risk; can’t DAG; “and also…”

Merge micro-tasks; split epics at real dependency or risk boundaries — not at arbitrary checklist length.

Related skills

  • Lost on what matters → idk-now
  • Tactical scout → recon
  • Code structure only → refactor-it
  • Issue/milestone scope → issues narrow / milestones narrow
  • Agent stacks → agents analyze|design|optimize (slap first if thrashing)
  • Docs bloat → DocSlime kiss / document-it as appropriate

Grounding

This skill’s TTPs are grounded in current engineering baselines (DORA, GitHub Docs, Fowler/Beck, Google SRE & SWE book, OpenTelemetry, OWASP LLM / NIST AI RMF, Diátaxis — see handbook sources.md).

Beck’s simple-design order (pass tests → reveal intent → remove duplication → fewer elements) and Gall’s Law: simplify when complexity is unearned, not by deleting needed safety. DORA loosely coupled architecture rewards deployable simplicity.

Handbook card: handbook/practices/kiss.md.

from this repository

More skills

All skills
decisionnerd
Community

agents

Work agent systems with command arguments: slap (emergency-fix stupid agent behavior and safely drain dumb workflows), analyze, optimize, design, and sub / sub-agents (delegate via subagents). Use when the user says agents, /agents , agent loops are thrashing, workflows need draining, or they want agent architecture, analysis, or parallel subagent execution.

1h installs
3
GitHub stars
0
Updated
Nov 4
decisionnerd
Community

architect-it

Design or evolve the architecture of a system, module, or feature — survey the codebase, frame the bet (boundaries, placement, data flow), propose options with tradeoffs, record the decision where the repo keeps decisions, and plan the first slice. Use when the user says "architect it", asks to design a system or module, review architecture, plan boundaries before building, or untangle a structural bet that refactoring alone cannot fix. Not for behavior-preserving mechanics (use refactor-it), co

1h installs
3
GitHub stars
0
Updated
Nov 4
decisionnerd
Community

check-readiness

Review whether a GitHub issue is complete enough for its current stage and decide the next PR or closure action. Use before PR, before closing an issue, after merge, or when auditing a closed issue for regressions or missing scope. For pre-PR checks, use CodeRabbit CLI review; when an open PR exists and corrective review work is needed, use autofix.

1h installs
3
GitHub stars
0
Updated
Nov 4
decisionnerd
Community

council

Convene independent reviews from three model providers and reconcile their findings. Use when the user says council, asks for a multi-model review, or wants several providers to challenge a plan or implementation.

1h installs
3
GitHub stars
0
Updated
Nov 4