landscape-jira

Creates well-formed Jira issues in the LNDENG project (warthogs.atlassian.net) — stories, epics, objectives, tasks, spikes, bugs, and more — with correct field mappings, sprint assignment, and acceptance criteria.

Quality

73%

Does it follow best practices?

Impact

—

No eval scenarios have been run

Securityby

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./groups/landscape/skills/landscape-jira/SKILL.md

Quality

Discovery

82%

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

This is a strong description with excellent specificity and distinctiveness, clearly naming the target system, project, and concrete actions. The main weakness is the absence of an explicit 'Use when...' clause, which would help Claude know exactly when to select this skill. The natural trigger terms are well-covered through the enumeration of issue types and Jira-specific terminology.

Suggestions

Add an explicit 'Use when...' clause, e.g., 'Use when the user asks to create a Jira ticket, file a bug, add a story, or set up an epic in the LNDENG project.'

Dimension	Reasoning	Score
Specificity	Lists multiple specific concrete actions: creating Jira issues across various types (stories, epics, objectives, tasks, spikes, bugs), with field mappings, sprint assignment, and acceptance criteria. Very concrete and detailed.	3 / 3
Completeness	Clearly answers 'what does this do' with detailed capabilities, but lacks an explicit 'Use when...' clause or equivalent trigger guidance. The when is only implied by the nature of the actions described.	2 / 3
Trigger Term Quality	Includes strong natural keywords users would say: 'Jira', 'issues', 'stories', 'epics', 'tasks', 'bugs', 'sprint', 'acceptance criteria', 'spikes', and the specific project name 'LNDENG'. These are terms users would naturally use when requesting this kind of work.	3 / 3
Distinctiveness Conflict Risk	Highly distinctive due to the specific project name (LNDENG), specific Jira instance (warthogs.atlassian.net), and the detailed enumeration of issue types. Very unlikely to conflict with other skills.	3 / 3
	Total	11 / 12 Passed

Implementation

64%

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

This is a strong, highly actionable skill with excellent concrete details — exact field IDs, JSON templates, JQL queries, and explicit error messages for common pitfalls. Its main weaknesses are the verbose AC guidance section (which teaches general product management rather than project-specific conventions) and the lack of an end-to-end workflow with verification steps after issue creation.

Suggestions

Add an end-to-end workflow section showing the complete sequence: look up sprint ID → construct issue payload → create issue via MCP → verify the created issue, with explicit validation after creation.

Trim the 'Writing Good Acceptance Criteria' section to project-specific conventions only (e.g., 'use declarative statements, group by type') and remove general PM concepts Claude already knows (what AC is, AC vs DoD philosophy).

Consider splitting JQL patterns and AC writing guidance into separate referenced files to keep the main SKILL.md focused on the core task of creating issues.

Dimension	Reasoning	Score
Conciseness	The skill is mostly efficient with good use of tables and concrete field mappings. However, the 'Writing Good Acceptance Criteria' section (~30 lines) explains general product management concepts that Claude already knows (what AC is, qualities of good AC, AC vs DoD). This section could be reduced to a few bullet points of project-specific conventions.	2 / 3
Actionability	Highly actionable throughout: exact field IDs, exact JSON formats for ADF, sprint, parent fields, executable JQL queries, and explicit error messages for common mistakes. Everything is copy-paste ready with concrete examples.	3 / 3
Workflow Clarity	The skill clearly documents individual field formats and gotchas, and the sprint lookup workflow is well-sequenced. However, there's no end-to-end workflow showing the full issue creation process (e.g., 1. look up sprint → 2. construct fields → 3. create issue → 4. verify creation succeeded), and no validation/verification step after issue creation.	2 / 3
Progressive Disclosure	The content is well-organized with clear section headers and tables, but it's a single monolithic file with no references to supporting files. The AC guidance section and JQL patterns could be split into separate reference files to keep the main skill leaner. For a skill of this length (~150 lines), some separation would improve navigability.	2 / 3
	Total	9 / 12 Passed

Validation

100%

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 — 11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository: canonical/copilot-collections
Commit: c5644f6

Reviewed: 4 days ago

Table of Contents

Discovery Implementation Validation

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