Name: deal-desk
Rating: 69.6 (1 reviews)
Author: alirezarezvani

deal-desk

Use when reviewing a specific inbound deal before close — when sales has asked for a discount that exceeds AE authority, when the customer has redlined the MSA, when per-deal economics (margin after discount, multi-year payment shape, indemnity exposure) need to be quantified, or when discount approval needs to be routed to a named human approver (Sales Director, VP Sales, CFO, CRO, General Counsel). Covers deal review, discount approval routing, per-deal margin scoring, deal exception handling, MSA redline triage, contract landmine detection (uncapped indemnity, MFN, perpetual license-back, missing DPA), and named-approver chain assembly. NEVER auto-approves — every output is a numeric scorecard plus a routing recommendation to a named human.

Quality

85%

Does it follow best practices?

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Securityby

Passed

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The canonical home for this skill is deal-desk in alirezarezvani/claude-skills

Quality

Content

78%Weight 40%Scale 1-5

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

The body is highly actionable with executable commands and a well-sequenced workflow, and it avoids over-explaining known concepts. Its main weakness is that the referenced bundle files (references/, scripts/, assets/) do not exist, breaking progressive-disclosure navigation, with a minor validation-loop gap in the workflow.

Suggestions

Ship the referenced bundle files (scripts/deal_scorer.py, scripts/discount_approval_router.py, scripts/terms_redliner.py, references/*.md, assets/deal_intake_template.md) or remove the references so navigation resolves.

Move the critical-signal override ('UNCAPPED_INDEMNITY blocks APPROVE') from Anti-patterns into the Workflow as an explicit gating checkpoint between the score and route steps.

Tighten the forcing-question library — the per-question canon citations could be condensed or moved to a reference file to reduce token load in the main body.

Dimension	Reasoning	Score
Conciseness	Mostly lean and assumes Claude's competence (no explanation of MSA/MFN/DPA), but the 7-item forcing-question library with per-question canon citations and verbose reference source lists add tokens that don't all earn their place.	4 / 5
Actionability	Provides copy-paste-ready commands ('python3 scripts/deal_scorer.py --input my_deal.json --profile enterprise-software', '--sample', '--output json') plus a scripts table documenting flags and profiles, covering the common cases.	5 / 5
Workflow Clarity	Clear 5-step sequenced workflow with per-step script invocations and a real validation gate (critical-signal override: 'A high composite with UNCAPPED_INDEMNITY is still a DECLINE'); the explicit validate-fix-retry loop is only implied and the override rule lives in anti-patterns rather than the workflow itself, leaving a minor checkpoint gap.	4 / 5
Progressive Disclosure	The overview is well-structured with clearly signaled one-level-deep references (references/deal_desk_canon.md, scripts/deal_scorer.py, assets/deal_intake_template.md), but none of the referenced bundle files or directories actually exist, so the navigation breaks.	3 / 5
	Total	16 / 20 Passed

Description

92%Weight 40%Scale 1-5

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 is specific, trigger-rich, and explicitly answers both what the skill does and when to use it, with a clear boundary against auto-approval. Trigger-term synonym coverage is strong but not exhaustive, the only dimension sitting just below the top anchor.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — 'deal review, discount approval routing, per-deal margin scoring, deal exception handling, MSA redline triage, contract landmine detection (uncapped indemnity, MFN, perpetual license-back, missing DPA), and named-approver chain assembly' — with comprehensive coverage; written in third person throughout.	5 / 5
Completeness	Explicitly answers both 'what' ('Covers deal review, discount approval routing...') and 'when' with an explicit 'Use when...' clause containing several concrete trigger phrases, matching the top anchor.	5 / 5
Trigger Term Quality	Includes natural trigger phrases a user would say ('asked for a discount that exceeds AE authority', 'redlined the MSA', 'routed to a named human approver', 'CFO, CRO, General Counsel'); good but not exhaustive synonym coverage, so just below the comprehensive anchor.	4 / 5
Distinctiveness Conflict Risk	Occupies a clear niche (per-deal review before close) with distinct triggers and an explicit 'NEVER auto-approves' boundary, giving minimal overlap with sibling skills.	5 / 5
	Total	19 / 20 Passed

Validation

87%

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 — 14 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning
referenced_paths_exist	Referenced path issues: 13 missing	Warning

	Total	14 / 16 Passed

Repository: alirezarezvani/claude-skills
Path: .gemini/skills/deal-desk/SKILL.md
Commit: 19392f7

Reviewed: ~5 hours ago

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