Borrowing it
Nothing to install: this file belongs to openshift/ols. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/openshift/ols/main/.claude/skills/estimate-story/SKILL.mdgit clone --depth 1 https://github.com/openshift/olsWrote 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.
[](https://agentmods.dev/skills/openshift/ols/estimate-story)<a href="https://agentmods.dev/skills/openshift/ols/estimate-story"><img src="https://agentmods.dev/badge/skills/openshift/ols/estimate-story.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00057 | $0.01667 |
| Opus 5 | $0.00028 | $0.00834 |
| Sonnet 5 | $0.00011 | $0.00333 |
| Haiku 4.5 | $0.00006 | $0.00167 |
Grade A, and why
estimate-story 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 2d 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.
How it starts
The opening of the file, as written. The whole thing — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Estimate Story Points for OLS Stories
Overview
Estimate story points for one or more OLS Jira stories using the team's calibrated rubric. After estimating, set the story points field and add an estimation comment.
Usage
/estimate-story OLS-1234
/estimate-story OLS-1234 OLS-1235 OLS-1236
Also invoked automatically after creating a new OLS story. Works for Stories, Bugs, Tasks, Weaknesses, and Vulnerabilities.
Rubric Location
Read the full rubric from: story-point-rubric.md (in the workspace root). Its "Calibrated
Rules (v11)" section is the authoritative correction layer (no 0; no 1→2 push; lean 2→3; 5
only with 2+ strong signals; no 8; plus the work-type defaults) and takes precedence over the
older point-definition prose / decision tree / bias-corrections.
You MUST read this file before estimating. It contains:
- Point definitions (0, 0.5, 1, 2, 3, 5) with characteristics and code complexity data
- Decision tree for base estimate
- Bias corrections from blind testing
- Complexity multipliers (up/down factors)
- Component-specific guidance
Workflow
Step 1: Read the rubric
Read story-point-rubric.md
Pay attention to its "Calibrated Rules (v11)" section — it is the authoritative correction layer and takes precedence over the older prose / decision tree / bias-corrections.
Step 2: Parse story keys from arguments
Extract all OLS-XXXX keys from the skill arguments. If no arguments
provided, ask the user for story key(s).
Step 3: For each story
3a. Fetch the story from Jira
Use mcp__plugin_atlassian_atlassian__getJiraIssue with:
cloudId:redhat.atlassian.netissueIdOrKey: the story keyresponseContentFormat:markdown
Extract: summary, description, components, labels, current story points value.
If story points are already set, tell the user and ask whether to re-estimate or skip.
Note: The rubric was built from Stories but applies to all issue types that use story points. For Weaknesses and Vulnerabilities, treat them like Bugs — the complexity is in the investigation + fix, not the issue type label.
What ships with it
2 files 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.
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.
- 2d ago Changed · +1 lines 70802b275c63
- 6d ago First seen · 166 lines · 57 tokens per session scan A 5540d536dabb
estimate-story is a skill published in the GitHub repository openshift/ols (2 stars, last pushed 3d ago), licensed Apache-2.0. It adds 57 tokens to every session and 1,667 once invoked, about $0.0003 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.
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