export-open-issues

Audit and export open issues from any project tracker with summary analysis and vault archival

Quality

37%

Does it follow best practices?

Impact

—

No eval scenarios have been run

Securityby

Advisory

Suggest reviewing before use

Optimize this skill with Tessl

npx tessl skill review --optimize ./.claude/skills/export-open-issues/SKILL.md

Quality

Discovery

32%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description conveys a general sense of the skill's purpose—auditing and exporting issues from project trackers—but lacks the specificity and explicit trigger guidance needed for reliable skill selection. It would benefit from concrete examples of supported trackers, clearer action descriptions, and an explicit 'Use when...' clause.

Suggestions

Add an explicit 'Use when...' clause, e.g., 'Use when the user wants to review, audit, or export open issues from a project tracker like Jira, GitHub Issues, or Linear.'

Include natural trigger terms users would actually say, such as 'Jira', 'GitHub issues', 'tickets', 'backlog', 'bug tracker', or 'task board'.

Clarify vague terms like 'vault archival' and 'summary analysis' with concrete actions, e.g., 'saves exported issues to an Obsidian vault' or 'generates a summary report with issue counts and priority breakdown'.

Dimension	Reasoning	Score
Specificity	Names several actions (audit, export, summary analysis, vault archival) and a domain (project tracker issues), but the actions are somewhat high-level and lack concrete detail about what 'audit' or 'vault archival' specifically entail.	2 / 3
Completeness	Describes what the skill does but completely lacks a 'Use when...' clause or any explicit trigger guidance for when Claude should select this skill. Per the rubric, a missing 'Use when...' clause caps completeness at 2, and since the 'what' is also somewhat vague, this scores a 1.	1 / 3
Trigger Term Quality	Includes some relevant terms like 'open issues', 'project tracker', 'export', and 'audit', but misses common natural variations users might say such as 'Jira', 'GitHub issues', 'bug tracker', 'tickets', 'backlog', or 'task management'.	2 / 3
Distinctiveness Conflict Risk	The combination of 'project tracker', 'open issues', and 'vault archival' provides some distinctiveness, but 'any project tracker' is broad and 'summary analysis' is generic enough to overlap with reporting or analytics skills.	2 / 3
	Total	7 / 12 Passed

Implementation

42%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The skill is highly actionable with concrete commands, tool names, and specific output formats, but it is severely over-engineered for a SKILL.md file. The complete report template, detailed agent prompts, and extensive table formats should be extracted into supporting files rather than inlined. The workflow is well-structured but lacks explicit validation checkpoints between phases.

Suggestions

Extract the full report markdown template into a separate file (e.g., REPORT-TEMPLATE.md) and reference it from the skill body to dramatically reduce token usage.

Extract the per-tracker agent prompts into separate files (e.g., GITHUB-COLLECTOR.md, LINEAR-COLLECTOR.md, JIRA-COLLECTOR.md) and reference them by name.

Add explicit validation checkpoints between phases — e.g., verify issue count matches expected range after collection, validate report structure before saving to vault.

Remove the text-based distribution chart examples and the exhaustive table column specifications; Claude can generate these from a brief description like 'produce priority and age distribution charts in text-bar format'.

Dimension	Reasoning	Score
Conciseness	The skill is extremely verbose at ~250+ lines. The full report template is spelled out in exhaustive detail with every table column and placeholder, which Claude could easily generate from a brief specification. The text-based chart examples, the complete markdown report template, and the detailed agent prompts all add significant token bloat. Much of this is template content that Claude already knows how to produce.	1 / 3
Actionability	The skill provides fully executable commands (gh issue list, gh pr list, JQL queries, bash mkdir), specific MCP tool names for Linear, concrete JSON field lists, and exact file paths for output. The guidance is copy-paste ready and leaves little ambiguity about what to execute.	3 / 3
Workflow Clarity	The 5-phase workflow is clearly sequenced and the fallback/error handling tables are helpful. However, there are no explicit validation checkpoints between phases — for example, no step to verify that collected data is complete or well-formed before analysis, and no verification that the saved file is correct. For a multi-step process involving external API calls and file writes, this is a gap.	2 / 3
Progressive Disclosure	The entire skill is a monolithic wall of text with no references to supporting files. The full report template (~80 lines), the detailed agent prompts, the CSV format, and the fallback tables could all be split into separate reference files. Everything is inlined, making the skill unnecessarily long and hard to navigate.	1 / 3
	Total	7 / 12 Passed

Validation

90%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 10 / 11 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	10 / 11 Passed

Repository: huytieu/COG-second-brain
Commit: 034af4c

Reviewed: 18 days ago

Table of Contents

Discovery Implementation Validation

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