strat-creator: Skill for Claude Code

.claude/skills/assess-strat/SKILL.md

assess-strat is a skill for Claude Code from opendatahub-io/strat-creator. It costs 26 tokens per session (2,161 once invoked), scanned A, original, Apache-2.0.

A guide for assessing software strategies against quality criteria using local strategy files and repository scripts. It supports reviewing one strategy or a whole directory of strategies.

In plain words
What is it for?
Use it to run single or batch strategy assessments and save the resulting reports.
Why use it?
It provides a repeatable review process and keeps assessment results organized for later reference.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: reads .claude/ paths.

This is opendatahub-io/strat-creator's own configuration. It tells Claude Code how to work on strat-creator 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 strat-creator configures →

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is "Bash(python3 scripts/assess-strat/preflight.py:*)",.

Reuse

Borrowing it

Nothing to install: this file belongs to opendatahub-io/strat-creator. 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/opendatahub-io/strat-creator/main/.claude/skills/assess-strat/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/opendatahub-io/strat-creator

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 assess-strat

README.md
[![agentmods](https://agentmods.dev/badge/skills/opendatahub-io/strat-creator/assess-strat/github.svg)](https://agentmods.dev/skills/opendatahub-io/strat-creator/assess-strat)
Your own site
<a href="https://agentmods.dev/skills/opendatahub-io/strat-creator/assess-strat"><img src="https://agentmods.dev/badge/skills/opendatahub-io/strat-creator/assess-strat/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 assess-strat

Your own site · 80×15
<a href="https://agentmods.dev/skills/opendatahub-io/strat-creator/assess-strat"><img src="https://agentmods.dev/badge/skills/opendatahub-io/strat-creator/assess-strat.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 26 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,161 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.
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 $0.00026 $0.02161
Opus 5 $0.00013 $0.01081
Sonnet 5 $0.00005 $0.00432
Haiku 4.5 $0.00003 $0.00216

Measured 7d ago against content hash f6dcab446045, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

assess-strat 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.

.claude/skills/assess-strat/SKILL.md · 171 lines

How it starts

The opening of the file, as written. The whole thing — 171 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Usage

/assess-strat artifacts/strat-tasks/RHAISTRAT-1469.md
/assess-strat artifacts/strat-tasks/
/assess-strat RHAISTRAT-1469

Instructions

Script Location

The assess-strat scripts are maintained in this repository under scripts/assess-strat/. Use that path for all script and rubric references.

Rules

  • No shell pipes or compound commands. Run all scripts as simple commands (e.g., python3 scripts/assess-strat/setup_run.py /path/to/strategies). Do not use |, &&, ;, 2>/dev/null, or redirects. The Bash tool returns command output as a string -- parse it programmatically in your logic, not with sed/awk/wc/grep pipelines.

Architecture

Single-input mode scores one strategy from a file path. Batch mode scores all strategies in a directory. Results are saved as individual files in a timestamped run directory. Strategies are local markdown files -- no Jira fetch needed.

Directory Structure
assessments/                             # in the project directory (persistent)
  20260415-143000/                       # timestamped run
    RHAISTRAT-1469.result.md
    queue.txt                            # pending keys (managed by next_batch.py)
    strat_dir.txt                        # path to source strategy directory
    scores.csv                           # generated by parse_results.py when complete
  current -> 20260415-143000             # symlink to active/latest run

/tmp/strat-assess/single/                # single-mode temp files
  RHAISTRAT-1469.result.md
Single input (file path or strategy key)

Detect the input type:

  • File path (starts with / or ./ or ~, or contains .md): Use the file directly.
  • Strategy key (matches [A-Z]+-\d+ or STRAT-\d+): Search for the corresponding .md file in common locations:
    1. artifacts/strat-tasks/{KEY}.md
    2. .context/strat-tasks/{KEY}.md
    3. Search with Glob: **/{KEY}.md

Then assess:

  1. Run python3 scripts/assess-strat/prep_single.py {KEY} to clean up stale result files and ensure the output directory exists.
  2. Spawn one background agent (model: opus, run_in_background: true, subagent_type: strat-scorer) with the launch prompt below, setting {DATA_FILE} to the resolved strategy file path and {RUN_DIR} to /tmp/strat-assess/single.
  3. Read the result from /tmp/strat-assess/single/{KEY}.result.md, wrap it with a header, and present it to the user.

Read the full file on GitHub · 171 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. 7d ago First seen · 171 lines · 26 tokens per session scan A f6dcab446045

Subscribe to this mod's changes

assess-strat is a skill published in the GitHub repository opendatahub-io/strat-creator (2 stars, last pushed 2d ago), licensed Apache-2.0. It adds 26 tokens to every session and 2,161 once invoked, about $0.0001 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 2026-09-04.

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