quinotospec-valkyrie

quinotospec-valkyrie is a skill for Claude Code, Codex from Quinoto-Tech/QuinotoSpec. It costs 40 tokens per session (712 once invoked), scanned A, original, MIT.

A backlog triage tool that ranks active proposals and decides which should be merged, continued, or archived.

In plain words
What is it for?
It helps prioritize proposals by impact, urgency, technical debt, risk, and dependency readiness, then shows the next action.
Why use it?
It reduces guesswork when several proposals compete for attention or overlap with each other.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It helps prioritize proposals by impact, urgency, technical debt, risk, and dependency readiness, then shows the next action.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/quinoto-tech/quinotospec/quinotospec-valkyrie
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Quinoto-Tech/QuinotoSpec --skill quinotospec-valkyrie
Clone the repo
git clone --depth 1 https://github.com/Quinoto-Tech/QuinotoSpec

Made for: Claude Code, Codex.

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 quinotospec-valkyrie

README.md
[![agentmods](https://agentmods.dev/badge/skills/quinoto-tech/quinotospec/quinotospec-valkyrie/github.svg)](https://agentmods.dev/skills/quinoto-tech/quinotospec/quinotospec-valkyrie)
Your own site
<a href="https://agentmods.dev/skills/quinoto-tech/quinotospec/quinotospec-valkyrie"><img src="https://agentmods.dev/badge/skills/quinoto-tech/quinotospec/quinotospec-valkyrie/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 quinotospec-valkyrie

Your own site · 80×15
<a href="https://agentmods.dev/skills/quinoto-tech/quinotospec/quinotospec-valkyrie"><img src="https://agentmods.dev/badge/skills/quinoto-tech/quinotospec/quinotospec-valkyrie.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 40 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 712 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 warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium analysis-evasion · line 1
    Suspicious Unicode normalization or mixed-script content
    Fix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
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 $0.00040 $0.00712
Opus 5 $0.00020 $0.00356
Sonnet 5 $0.00008 $0.00142
Haiku 4.5 $0.00004 $0.00071

Measured 9d ago against content hash 2ef486ff644f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

quinotospec-valkyrie 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 9d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (rank.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

agent-dist/skills/quinotospec-valkyrie/SKILL.md · 61 lines

How it starts

The opening of the file, as written. The whole thing — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill: Quinotospec Valkyrie — La Electora de los Caidos

Valkyrie elige en el campo de batalla. Esta skill elige en tu backlog.

Cuando usar

  • quinotospec.status muestra 3+ propuestas activas y no sabes cual priorizar
  • conflict-detector reporta solapamiento — Valkyrie decide orden de merge
  • Como input a sprint.plan para ranking

Invocacion

/quinotospec-valkyrie                          # rankea propuestas activas
/quinotospec-valkyrie --suggest-next           # integra suggest-next global
/quinotospec-valkyrie --json                   # output machine-readable

Comportamiento

Scoring (0-100)

score = 0.30*impact + 0.25*urgency + 0.20*risk_inverse + 0.15*debt_relief + 0.10*deps_ready
  • impact: # servicios afectados + # US P1 (de user-stories.md)
  • urgency: antiguedad + label priority: P1 en proposal.md
  • risk_inverse: 1 - DREAD_avg/10 (de Heimdallr si existe, sinon 0.5)
  • debt_relief: si proposal toca 07-findings o tiwaz-rune hallazgo → +20
  • deps_ready: artifact-engine status ready vs blocked (DAG)

Output

Tabla rankeada:

# | Propuesta | Score | Impact | ΔS | Conflictos | Next Action
1 | 2026-08-28-auth-jwt (AUTH-a1b2) | 84 | 3 svcs | +0.02 | none | ready → sprint.plan
2 | 2026-08-20-pay-v2 (PAY-c3d4)   | 62 | 2 svcs | +0.08 | solapa PAY-a9 | blocked (needs delta-specs)
3 | 2026-07-01-legacy (LEG-x1)     | 31 | 1 svc  | -    | stale 60d | candidate archive
  • Next Action mapeado: readysuggest-next, blocked → que falta, stale (>60d sin update) → archive candidato, conflictconflict-detector detail

Integracion

  • Lee proposals/*/proposal.md frontmatter + user-stories.md + tiwaz-rune/*.json + conflict-detector output
  • No requiere LLM — solo parsing + formula
  • status.md puede invocar Valkyrie como seccion "Prioridad Valhalla"

Reglas

  • Nunca auto-archiva — solo sugiere con candidate archive y requiere confirmacion
  • Si hay ciclo Jormungandr, score deps_ready = 0 y alerta BLOCKING

Read the full file on GitHub · 61 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 9d ago First seen · 61 lines · 40 tokens per session scan A 2ef486ff644f

Subscribe to this mod's changes

quinotospec-valkyrie is a skill published in the GitHub repository Quinoto-Tech/QuinotoSpec (20 stars, last pushed yesterday), licensed MIT. It adds 40 tokens to every session and 712 once invoked, about $0.0002 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 2026-09-03.

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