Claude-Mind: Skill for Claude Code

.claude/skills/sprint-planning/SKILL.md

sprint-planning is a skill for Claude Code from zkysar1/Claude-Mind. It costs 138 tokens per session (3,270 once invoked), scanned A, original, MIT.

A structured planning workflow for a software team’s work queues, where queues are lists of pending goals or tasks. It measures current work, analyzes priorities, checks proposed changes, applies verified updates, and publishes the resulting plan.

In plain words
What is it for?
Use it to plan a sprint across agents, review priorities and standing instructions, find duplicates or stalled work, reclaim incorrectly routed tasks, and apply verified queue improvements.
Why use it?
It turns reports into checked changes to the work queues rather than leaving planning as a document only. Verification helps catch duplicate goals, incorrect priorities, unhealthy recurring work, and other queue problems.

Skill for Claude Code

Written for Claude Code: user-invocable in frontmatter.

This is zkysar1/Claude-Mind's own configuration. It tells Claude Code how to work on Claude-Mind itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything Claude-Mind configures →

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is Bash: MIND_AGENT=<A> bash core/scripts/goal-selector.sh select.

Reuse

Borrowing it

Nothing to install: this file belongs to zkysar1/Claude-Mind. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/zkysar1/Claude-Mind/main/.claude/skills/sprint-planning/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/zkysar1/Claude-Mind

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for sprint-planning

README.md
[![agentmods](https://agentmods.dev/badge/skills/zkysar1/claude-mind/sprint-planning/github.svg)](https://agentmods.dev/skills/zkysar1/claude-mind/sprint-planning)
Your own site
<a href="https://agentmods.dev/skills/zkysar1/claude-mind/sprint-planning"><img src="https://agentmods.dev/badge/skills/zkysar1/claude-mind/sprint-planning/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for sprint-planning

Your own site · 80×15
<a href="https://agentmods.dev/skills/zkysar1/claude-mind/sprint-planning"><img src="https://agentmods.dev/badge/skills/zkysar1/claude-mind/sprint-planning.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 138 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,270 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00138 $0.03270
Opus 5 $0.00069 $0.01635
Sonnet 5 $0.00028 $0.00654
Haiku 4.5 $0.00014 $0.00327

Measured 10d ago against content hash 951df30ce871, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

sprint-planning scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/skills/sprint-planning/SKILL.md · 263 lines

How it starts

The opening of the file, as written. The whole thing — 263 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/sprint-planning — Fleet Sprint Planning Exercise

Turns the two report skills into a full planning pass: measure → analyze → verify → apply → publish. A plan that changes no queue state is a report, not a plan (asp-353 directive lineage) — but every queue change must survive a live-state verification first. Formalized 2026-08-10 from a user-directed sprint session (74-agent ultracode pass, 276 proposed changes, 28 refuted by adversarial verification — the refutation rate is why Phase 4's verify step is not optional).

Hybrid skill: user-invocable AND agent-callable (the recurring sprint-planning goal invokes it in standard mode). Requires assistant or autonomous mode — it writes queue state.

Sub-commands

/sprint-planning            — Standard pass: inline analysis, bounded lanes
/sprint-planning --ultra    — USER-INVOKED ONLY: authorizes a multi-agent
                              Workflow fan-out (per-aspiration analysts +
                              adversarial verifiers). An agent-initiated
                              (recurring-goal) run MUST NOT pass --ultra:
                              Workflow orchestration requires explicit user
                              opt-in, and a recurring firing is not one.

Phase 0: Load Conventions

Step 0: Load ConventionsBash: load-conventions.sh with each name from the conventions: front matter. Read only the paths returned (files not yet in context). If output is empty, all conventions already loaded — proceed to next step.

Phase 1: Foundation Reports

1. Invoke Skill(backlog-report) — produces agents/<agent>/BACKLOG.md and the
   structural indexes this skill reuses (score map, blocked map, user goals,
   recurring health, testable hypotheses).

2. Priority dashboard data (inline — do NOT invoke /priority-review here; its
   Phases 3-4 are interactive and this skill's reorder decisions come from
   Phase 3 analysis instead):
   Bash: load-aspirations-compact.sh → Read returned path
   Bash: goal-selector.sh select → scored_goals (NOTE: output is a bare JSON
     array, not a dict) → aggregate score per aspiration
   Bash: echo '<[{asp_id,priority,score}...]>' | priority-review-mismatch.sh
     → flagged score-priority mismatches (needs 3+ consecutive runs to flag)

3. Snapshot for the ledger: record counts (active aspirations, non-terminal
   goals, selectable goals, blocked, user-routed, overdue recurring) BEFORE
   any write — these are the plan's before/after evidence.

Read the full file on GitHub · 263 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 10d ago First seen · 263 lines · 138 tokens per session scan A 951df30ce871

Subscribe to this mod's changes

sprint-planning is a skill published in the GitHub repository zkysar1/Claude-Mind (5 stars, last pushed 2d ago), licensed MIT. It adds 138 tokens to every session and 3,270 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other skills, from other repositories

hive.browser-automation

Required before any hive-browser CLI command. The browser is driven from the terminal by running hive-browser ... --json via terminalexec — not via MCP tools. Teaches the browser lifecycle rules (the bridge attaches to the USER'S running Chrome — never kill or launch browser processes; timeouts are transport issues…

aden-hive/hive · 142 tokens

hive.worker-delegation

Concrete patterns for breaking colony work into parallel worker jobs via runplaybook — when fan-out helps, how to model the goal as a tracker table, write the worker skill, author the playbook, pilot, and let convergence retry/resume the gap.

aden-hive/hive · 58 tokens

hive.linkedin-automation

Read before automating LinkedIn with browser tools. LinkedIn combines shadow DOM (#interop-outlet), strict Trusted Types CSP that silently drops innerHTML, Lexical composer, native beforeunload dialogs that hang the bridge, and aggressive spam filters — each has bitten us at least once. Verified flows for profile…

aden-hive/hive · 99 tokens

hive.x-automation

Read before automating X / Twitter with browser tools. Verified flows for post, reply, delete, search-and-engage, plus the Draft.js compose quirks that silently disable the send button. Includes the daily-reply and job-market-reply playbooks. Requires hive.browser-automation for the underlying screenshot + coordinate…

aden-hive/hive · 81 tokens

hive.slack-notifications-setup

Set up a Slack notification channel (Sentinel) for a colony by driving the browser — reuse or create the "Hive Sentinel" Slack app from a JSON manifest, install it, capture the bot + app tokens, create/select the channel via the Slack API, and turn Sentinel on so the colony can ping the user on Slack and accept…

aden-hive/hive · 136 tokens

hive.pdf

Read, write, merge, split, rotate, watermark, encrypt, and OCR PDF files using Python (pypdf, pdfplumber, reportlab, pypdfium2) and command-line tools (poppler-utils, qpdf). Use when the user asks to extract text/tables/images from a PDF, create or modify a PDF, combine or split PDFs, OCR a scanned PDF…

aden-hive/hive · 98 tokens