ralph-specum-research

ralph-specum-research is a skill for Codex from tzachbon/smart-ralph. It costs 43 tokens per session (1,172 once invoked), scanned A, original, MIT.

A research workflow for Ralph Specum, a system that plans software work through written specifications. It coordinates research by delegating it to a separate research worker.

In plain words
What is it for?
Use it to research an active specification, review its progress and related work, and prepare research findings for the next planning phase.
Why use it?
It helps gather and organize information for an existing specification before design or implementation begins.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: mentions subagents; mentions Codex; $skill-name invocation.

Good fit Use it to research an active specification, review its progress and related work, and prepare research findings for the next planning phase.

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Install with agentmods
npx agentmods add skills/tzachbon/smart-ralph/ralph-specum-research
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 tzachbon/smart-ralph --skill ralph-specum-research
Clone the repo
git clone --depth 1 https://github.com/tzachbon/smart-ralph

Made for: 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 ralph-specum-research

README.md
[![agentmods](https://agentmods.dev/badge/skills/tzachbon/smart-ralph/ralph-specum-research/github.svg)](https://agentmods.dev/skills/tzachbon/smart-ralph/ralph-specum-research)
Your own site
<a href="https://agentmods.dev/skills/tzachbon/smart-ralph/ralph-specum-research"><img src="https://agentmods.dev/badge/skills/tzachbon/smart-ralph/ralph-specum-research/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 ralph-specum-research

Your own site · 80×15
<a href="https://agentmods.dev/skills/tzachbon/smart-ralph/ralph-specum-research"><img src="https://agentmods.dev/badge/skills/tzachbon/smart-ralph/ralph-specum-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 43 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,172 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 Agent Snooping · line 29
    Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.
    Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 $0.00043 $0.01172
Opus 5 $0.00022 $0.00586
Sonnet 5 $0.00009 $0.00234
Haiku 4.5 $0.00004 $0.00117

Measured 7d ago against content hash e70d64f7e1e0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

ralph-specum-research 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 7d 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.

plugins/ralph-specum-codex/skills/ralph-specum-research/SKILL.md · 59 lines

How it starts

The opening of the file, as written. The whole thing — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Ralph Specum Research

You are a coordinator, not a researcher -- delegate ALL work to a research-analyst sub-agent.

Derive RALPH_CODEX_PLUGIN_ROOT from this loaded skill by resolving two parent directories from the SKILL.md directory. Never derive it from the project working directory.

Contract

  • Resolve the active spec by explicit path, exact name, or .current-spec
  • Respect .claude/ralph-specum.local.md when present
  • Default specs root is ./specs
  • Keep the canonical Ralph file names
  • Merge state fields only

Action

  1. Resolve the active spec. If none exists, stop and tell the user to start a spec first.
  2. Read the goal, .progress.md, current state, indexed codebase context, related specs, and epic context when present.
  3. Run phase_gate.py mode through "$RALPH_CODEX_PLUGIN_ROOT/scripts/phase_gate.py" with STATE and exact --quick, exact --interactive, or no flag. Reject both, -q, variants, and natural-language substitutes.
  4. Run skill discovery pass 1 when the state lacks an applicable revision. Select explicitly named skills and record harness-shadowed duplicates.
  5. Load "$RALPH_CODEX_PLUGIN_ROOT/skills/interview-framework-codex/SKILL.md", its required algorithm and domain-modeling references, and all selected domain contracts in both interactive and quick mode. In interactive mode, use its focused brainstorming method for critical evidence scope, decision thresholds, and material unknowns. Inspect source availability, code facts, and existing patterns instead of asking.
  6. In interactive mode, require explicit approve and delegate; in exact quick mode, record bypassed_quick. In both modes, run phase_gate.py check-delegation with the current loaded-manifest identity before creating the child. Apply the shared hard-transition invariant before research writer dispatch. A failed check-delegation in either mode stops this invocation before phase transition, child dispatch, or target-artifact write; after a normal-mode failure, only the next explicit invocation creates a fresh manifest/interview identity. After an exact --quick delegation failure, the next explicit invocation reruns discovery, records a fresh phaseSkillLoad and interview identity, and does not reuse a terminal bypassed_quick interview or its discovery revision. Only a matching in-progress collecting or awaiting_confirmation interview is resumable. Exact --quick retains its existing question-and-approval bypass and discovery, manifest, delegation, and writer checks.
  7. Delegate research generation to a research-analyst sub-agent. Keep the existing child packet, identity tuple, and receipt behavior unchanged: pass the absolute gate helper path, state path, full identity tuple, unique teammate dispatch identity, verbatim skill manifest, goal, context, and interview results. The sub-agent reloads and records the manifest, passes check-agent-write with that unique identity, and writes research.md. Do NOT write research.md yourself.
  8. Read the sub-agent's output and validate it exists.
  9. Merge state with phase: "research" and awaitingApproval: true (or false when exact --quick is active).
  10. Update .progress.md with the research summary, blockers, learnings, next step, skill discovery, and verification tooling notes when relevant.
  11. If spec commits are enabled, commit only the spec artifacts.
  12. In normal mode, when the user selects continue to prototype, treat research.md as approved and route to $ralph-specum-prototype --suggested --return-phase requirements with the same resolved base path. Let that skill own prototype behavior and its return handoff.

Read the full file on GitHub · 59 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. 7d ago Changed e70d64f7e1e0
  2. 11d ago First seen · 59 lines · 43 tokens per session scan A 774ca8060159

Subscribe to this mod's changes

ralph-specum-research is a skill published in the GitHub repository tzachbon/smart-ralph (536 stars, last pushed today), licensed MIT. It adds 43 tokens to every session and 1,172 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 2026-08-30.