zprolab
WhaleKit
Superpowers customized for DeepSeek Harness
- Stars
- 1
- Language
- Shell
- Created
- Aug 14, 2026
- Updated
- Aug 14, 2026
Introduction
WhaleKit
WhaleKit is an agentic skills framework for DeepSeek Harness (DSH). It is a collection of
composable, DSH-native SKILL.md skills plus an entry skill that ensures agents use them — built for
full autonomy from upstream roadmaps and hardened against hallucination with an adversarial review
mechanism.
Together with install.sh, it replaces binary skill invocation (Superpowers' weakness) with a
five-tier routing ceremony: process depth is chosen per task, from none at L1 up to full ceremony
at L5. Git is the traceability layer; every authoritative document is amendable but every amendment
is a commit.
Quick Start
1. Install
From the repository root, run the installer:
./install.sh # install into ~/.dsh/skills (DSH_HOME overrides the root)
./install.sh --project # install into <project>/.dsh/skills instead
./install.sh --uninstall # remove every WhaleKit skill symlink (works with --project too)
- Default: symlinks all 22 skills into
$DSH_HOME/skills(defaults to~/.dsh/skills). --project: symlinks into<projectRoot>/.dsh/skills, which DSH ranks above the home root.--uninstall: removes every WhaleKit symlink and the emptied target directory.- Options are order-independent (
install.sh --uninstall --projectbehaves identically).
DSH discovers skills from <projectRoot>/.dsh/skills (rank 100) before ~/.dsh/skills (rank 400),
so a project-local install takes precedence over a global one.
2. First session
using-whalekit is the entry skill: it must be invoked at the start of any conversation. After
using-whalekit, invoke whalekit-conventions (mandatory) — the canonical global-conventions skill
that binds every agent, including subagents, before any task work begins. When you begin a task,
WhaleKit will classify it (trivial vs non-trivial), run targeted-exploration if needed, recommend a
routing tier, and present 2–3 tier options for you to choose. The user's decision is the highest
authority below the system prompt — the agent never picks the tier alone.
The Five Tiers
WhaleKit replaces binary skill invocation with a graduated routing menu. Process depth is chosen per task, from none at L1 up to full ceremony at L5. Core flow:
Session start → using-whalekit (mandatory entry)
→ Task assessment: is exploration needed?
├─ Trivial task (one-line fix) → artifact chain at Q1
└─ Non-trivial task → targeted-exploration (target = task core or whole project)
→ Exploration report: findings + evidence + risks + scope estimate
→ Main agent applies routing: asks the artifact chain one question at a time
(Q1 memo? → Q2 spec? → Q3 plan? → Q4 dual?)
→ User answers each question (gold standard)
→ Skills gated by reached tier → execution
| Tier | Process | Trigger signals (from exploration report) |
|---|---|---|
| L1 Immediate implementation | No process | Purely mechanical change, minimal risk |
| L2 Memo only | Memo persisted to disk | Small feature, single file |
| L3 Memo → Spec | + specification | Medium feature, touches interfaces |
| L4 Memo → Spec → Plan | + implementation plan | Large feature, multiple files/modules |
| L5 Full | + dual records | New project, architecture-level, directional decisions |
The tier is reached one question at a time via the artifact chain — the tier = how far the chain went (memo → spec → plan → dual records, one question at a time): a "no" at Q1 stops at L1, memo-only at L2, memo + spec at L3, memo + spec + plan at L4, and dual records at L5.
Iron rules of routing:
- User is the gold standard. Any tier recommendation must present 2–3 options; the user chooses. The agent never decides the tier alone.
- One-way ratchet. Hidden complexity discovered mid-task upgrades the tier — stop, say so, step up. Nothing downgrades mid-task.
- Exploration before recommendation. Tier recommendations for non-trivial tasks must be based on a targeted-exploration report, never on impression.
Skill Inventory
22 skills (9 original + 13 adapted). Adapted skills retain their
Adapted from obra/superpowers (MIT) header; see individual SKILL.md headers for attribution.
| Skill | Source |
|---|---|
using-whalekit | original — entry skill, routing startup |
whalekit-conventions | original — canonical global conventions binding all agents |
targeted-exploration | original — subagent-driven anti-divergence exploration feeding routing |
routing | original — five tiers, gating, one-way ratchet |
adversarial-review | original — red/blue/black meta-skill (decision + review modes) |
dual-records | original — DEVELOPMENT.md + README.md (amendable truth) |
commit | original — commit strategy gate + logical commit procedure |
clarification-questioner | original — question-asking methodology: generate → curate → ask one at a time → converge answers into a verified conclusion sheet (clarity/quality checked) before design |
decision-approval | original — waived decisions become a draft sheet (proposal/rationale/alternatives/confidence) the user approves or edits before they take effect |
socratic-brainstorming | adapted (heavy) — from obra/superpowers brainstorming |
test-driven-development | adapted — from obra/superpowers |
systematic-debugging | adapted — from obra/superpowers |
verification-before-completion | adapted — from obra/superpowers |
requesting-code-review | adapted — from obra/superpowers |
receiving-code-review | adapted — from obra/superpowers |
using-git-worktrees | adapted — from obra/superpowers |
finishing-a-development-branch | adapted — from obra/superpowers |
writing-plans | adapted — from obra/superpowers |
executing-plans | adapted — from obra/superpowers |
subagent-driven-development | adapted — from obra/superpowers |
writing-skills | adapted — from obra/superpowers (skill TDD) |
dispatching-agents | adapted — from obra/superpowers (generic delegation protocol; re-scoped 2026-08-14 from the parked parallel clone) |
Design Philosophy
- User is the gold standard. The user's decision is the highest authority below the system prompt. Every major decision presents 2–3 options; the agent never decides alone.
- Ceremony scales with task. Process depth is graduated (5 tiers) and chosen per task; small tasks get small process. The direct answer to Superpowers' binary-invocation problem.
- Fight hallucination with adversarial review. Big decisions and architecture-level bugs go through red/blue/black subagent loops (decision mode) and review-mode red-finds/blue-fixes loops, not single-agent judgment.
- Amendable truth. Review baselines (README.md in dual records) are authoritative but explicitly amendable, with every amendment traced in git.
All documents form a golden-standard chain — Dual → Plan → Spec → Memo → User requirement — where
the user requirement is the highest authority and live user decisions outrank the chain. Process
artifacts enter git by consent: every artifact write is preceded by a commit-policy check.
Installation
A single install.sh symlinks the skills into the DSH root, with --project (project-local
.dsh/skills) and --uninstall modes. See Quick Start.
Testing
Skill TDD via pressure scenarios in tests/pressure/<skill>/ — each skill has ≥2 scenarios (one
skip-temptation, one misleading-execution) plus pass-criteria.md. Run the harness:
tests/run.sh <skill> # print the scenario prompt and pass criteria
tests/run.sh <skill> --dispatch # print a ready-to-use subagent dispatch prompt
tests/run.sh <skill> --live # print a manual live-session verification checklist
--live exists for entry-sensitive skills (whose ceremony a dispatched subagent is correctly
exempted from by a <SUBAGENT-STOP> block) and any skill requiring live user interaction.
Roadmap
- v0.1 (current): DSH-only, coding domain, 22 skills, five-tier routing.
- v0.2 (planned — 2026-08-14 decision): multi-runtime planning. DSH-only is a concentration risk (SuperPowers ports to many harnesses); evaluate adapting the skill set to other harnesses to reduce single-runtime exposure. Scope and timeline TBD by a spec-level decision.
License
MIT. Portions adapted from obra/superpowers (MIT);
see individual SKILL.md headers for attribution.