Agent skill

Client Validation Document

by indranilbanerjee in indranilbanerjee/digital-marketing-pro

Produce the Part 5 Client Validation Document — the one true stop of the 12-Part engagement where unbiased v1 findings from Parts 2-4 are compiled into 12-25 evidence-cited finding blocks, each…

MITAuto-check: notes

Install Client Validation Document

skills CLI
$ npx skills add indranilbanerjee/digital-marketing-pro --skill client-validation-document -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install indranilbanerjee/digital-marketing-pro client-validation-document --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/indranilbanerjee/digital-marketing-pro.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/client-validation-document .claude/skills/client-validation-document && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
client-validation-document
GitHub stars
854
Used in
1 other repo
Token cost
~3.5k tokens
SKILL.md length
1,176 words
Files
1
Skills in repo
162
Repo updated
First seen
Licence
MIT

At a glance

Produce the Part 5 Client Validation Document — the one true stop of the 12-Part engagement where unbiased v1 findings from Parts 2-4 are compiled into 12-25 evidence-cited finding blocks, each…

  • Works in 3 steps: Parts 2, 3, 4 must be completed (or… → The engagement state file… → The Living Project Instruction File…
  • /digital-marketing-pro:client-validation-document
  • SKILL.md covers Context efficiency, What this document is, What this document is NOT and Pre-conditions, plus 10 more sections
  • Calls python

What it does

Client Validation Document is an agent skill from indranilbanerjee/digital-marketing-pro. Produce the Part 5 Client Validation Document — the one true stop of the 12-Part engagement where unbiased v1 findings from Parts 2-4 are compiled into 12-25 evidence-cited finding blocks, each awaiting an ACCEPT / REJECT / EDIT / DEFER client decision, plus a paired JSON response template. Recorded responses feed the Part 6 Decision Matrix (engagement-state.py) to determine v2 re-runs. Triggers on "/digital-marketing-pro:client-validation-document", "prepare v1 findings for client review", "run part 5 client…

Its SKILL.md is about 3.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: An open-source AI marketing operating system for strategy, SEO, AEO/GEO, paid media, content, CRM, and analytics - grounded in brand context, human approval, and verifiable… The licence is MIT.

When your agent uses it

  • /digital-marketing-pro:client-validation-document
  • Prepare v1 findings for client review
  • Run part 5 client validation
  • The one true stop

Example prompts

  • “/digital-marketing-pro:client-validation-document”
  • “prepare v1 findings for client review”
  • “run part 5 client validation”
  • “/client-validation-document”

Requirements

  • Python 3
  • Pre-approved tools (allowed-tools): Read, Write, Edit, Bash, Glob, Grep

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. Parts 2, 3, 4 must be completed (or substantially complete with explicit acknowledgment that some research continues)
  2. The engagement state file _engagement.json must show Parts 3 and 4 as completed
  3. The Living Project Instruction File should be up to date with the v1 strategic facts

What it can do on your machine

Read from SKILL.md and the folder at commit 3343924. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit
    • Bash
    • Glob
    • Grep

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Client Validation Document loads about 3.5k tokens when it runs. Until then it costs about 203 tokens; SKILL.md has 1,176 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~203
When it runs · the whole SKILL.md, loaded when a task matches
~3.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Read, Write, Edit, Bash, Glob, Grep

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from indranilbanerjee/digital-marketing-pro at commit 3343924, republished under its MIT licence (© indranilbanerjee). 1,176 words, ~3,473 tokens.

Download SKILL.mdSave it as .claude/skills/client-validation-document/SKILL.md (or your agent's skills folder).
name
client-validation-document
description
Produce the Part 5 Client Validation Document — the one true stop of the 12-Part engagement where unbiased v1 findings from Parts 2-4 are compiled into 12-25 evidence-cited finding blocks, each awaiting an ACCEPT / REJECT / EDIT / DEFER client decision, plus a paired JSON response template. Recorded responses feed the Part 6 Decision Matrix (engagement-state.py) to determine v2 re-runs. Triggers on "/digital-marketing-pro:client-validation-document", "prepare v1 findings for client review", "run part 5 client validation", "the one true stop", "record the client's validation responses". Requires Parts 3-4 marked completed in _engagement.json; reads the eight v1 core documents; pairs with /digital-marketing-pro:engagement-workflow and /digital-marketing-pro:four-core-documents.
allowed-tools
Read, Write, Edit, Bash, Glob, Grep
user-invocable
true
engagement-part
5
view-preference
v1-only

/digital-marketing-pro:client-validation-document — Part 5: The One True Stop

This skill produces the Part 5 deliverable: the Client Validation Document. It is the only point in the engagement where unbiased v1 findings are formally presented to the client for accept/reject/edit decisions.

Context efficiency

Heavy skill. Grep before Read any referenced file, then Read only matched ranges with offset + limit. List ${CLAUDE_PLUGIN_DATA}/<brand>/ before opening files. On re-invocation mid-session, skip files already in context.

This is the one true stop in the 12-Part flow. Nothing in Parts 6+ proceeds until this is signed off.

What this document is

The Client Validation Document compiles the most strategically consequential findings from Parts 2, 3, and 4 (the unbiased research and the four core documents) into a structured review document. For each finding:

  • The finding itself
  • Evidence / sources
  • Proposed implication if accepted
  • Three response options for the client: ACCEPT / REJECT / EDIT / DEFER
  • (For REJECT or EDIT) — the client provides their corrected version and the rationale

The client's responses then feed the Decision Matrix in Part 6 to determine which v2 re-runs are needed.

What this document is NOT

  • Not a Growth Plan. This is research findings, not strategic recommendations dressed up. The Growth Plan is Part 8.
  • Not exhaustive. It includes only findings that have material strategic implications. Detail belongs in the source documents.
  • Not a slide deck. It is a written document the client reads carefully and responds to. Slides do not capture the rigor required.
  • Not optional. Every engagement runs Part 5. No shortcut to Part 6 without it.

Pre-conditions

Before running this skill:

  1. Parts 2, 3, 4 must be completed (or substantially complete with explicit acknowledgment that some research continues)
  2. The engagement state file _engagement.json must show Parts 3 and 4 as completed
  3. The Living Project Instruction File should be up to date with the v1 strategic facts

If pre-conditions fail, do NOT produce output. Instruct the user on what is missing.

Document Structure

The Client Validation Document is organised by category of finding. Each category has 3–8 findings; total document is typically 12–25 findings across categories.

Section 1: Executive Briefing

Length: 1 page.

Content:

  • Purpose of this document
  • How to read it (the ACCEPT / REJECT / EDIT / DEFER framework)
  • What happens after the client responds (Part 6 v2 re-runs governed by the Decision Matrix)
  • Decision deadline (typically 7–14 days)
Section 2: Findings — by category

Each category contains its findings as structured blocks. Categories:

A. Business & SBU Findings (from 3.1)

Findings about the business reality — SBU separation, unit economics, value chain, growth levers, constraints, risks. Typically 3–5 findings.

B. Audience & Segmentation Findings (from 3.2 + 4.3)

Findings about target groups, persona priority, decision-making units, MQL/SQL definitions. Typically 3–5 findings.

C. Positioning & Communications Findings (from 3.3)

The chosen positioning, messaging pillars, tone-of-voice, don't-say rules, sensitive-topic handling. Typically 3–5 findings.

D. Channel & Budget Findings (from 3.4)

Channel selections, in-market vs out-market split, budget allocation, channel sequencing. Typically 2–4 findings.

E. Competitive Findings (from 4.1 + 4.2)

Competitor list, competitive positioning, Three-Question outputs (do well / do poorly / not doing). Typically 2–4 findings.

F. Market & Customer Findings (from 4.3 + 4.4)

Market sizing, customer behaviour patterns, demand signals. Typically 2–4 findings.

Section 3: Open Questions

Questions that the unbiased research could not resolve and need client input. The client provides answers here.

Section 4: Response Mechanism

How the client returns their responses (typically a structured response file or a meeting walkthrough).

Finding Block Format

Each finding follows this exact structure:

markdown
### Finding {ID}: {Short title}

**Category:** {A/B/C/D/E/F}
**Source:** {Document and step references — e.g., "3.1 Step 4, 4.1 Three-Question Output"}
**Materiality:** {High / Medium / Low}

**Finding:**
{2–4 sentences stating the finding from the unbiased research}

**Evidence:**
- {Cited source 1 with specific data point}
- {Cited source 2}
- {Cited source 3}

**Proposed implication if accepted:**
{1–3 sentences on what this means for the strategy if the client accepts}

**Client response:**

- [ ] ACCEPT — finding is correct as stated
- [ ] REJECT — finding is wrong; correction below
- [ ] EDIT — finding is partially correct; amended version below
- [ ] DEFER — needs further investigation; reason below

**If REJECT or EDIT, client correction:**
{Client fills in: what the correct finding is, with their evidence}

**If DEFER, reason and follow-up plan:**
{Client fills in: what additional research / data is needed, who is accountable, deadline}

Materiality Classification

Each finding gets a Materiality rating that indicates how consequential the response is:

  • High — accepting vs rejecting would meaningfully change the channel mix, budget, positioning, or audience priority. Triggers v2 re-runs per Decision Matrix.
  • Medium — accepting vs rejecting would change tactical execution but not strategic direction. May or may not trigger re-runs.
  • Low — accepting vs rejecting changes phrasing or examples but not substance. No re-run triggered.

The client should focus most attention on High materiality findings; Medium and Low are still presented for completeness.

Show full SKILL.md (522 more words)Show less

Response Categorisation for the Decision Matrix

After the client provides responses, the responses are categorised into Decision Matrix triggers:

Client decision patternDecision Matrix trigger
Any competitor finding REJECTED or EDITED with new competitorscompetitors_changed
Any market sizing finding REJECTED or EDITEDtarget_market_changed
Any segmentation finding REJECTED or EDITED with persona changesaudiences_changed
Any positioning finding REJECTED or EDITEDpositioning_changed
Any budget / scope finding REJECTED or EDITEDbudget_or_scope_changed
Any pricing or offering finding REJECTED or EDITEDpricing_or_offering_changed
Any unit economics finding REJECTED or EDITEDunit_economics_changed
Only Low-materiality EDITs / minor wording correctionsminor_corrections_only

The skill compiles the trigger list and runs:

bash
python ${CLAUDE_PLUGIN_ROOT}/scripts/engagement-state.py decision-matrix \
  --brand {slug} --id {id} \
  --triggers "{comma-separated-trigger-list}"

The output then feeds the Part 6 v2 re-run plan.

Production Steps

  1. Verify pre-conditions — Parts 2, 3, 4 completed.

  2. Read the v1 source documents:

    • part-03-four-core-documents/v1/3.1-business-and-sbu-analysis.md
    • part-03-four-core-documents/v1/3.2-segmentation-framework.md
    • part-03-four-core-documents/v1/3.3-brand-positioning-and-communications.md
    • part-03-four-core-documents/v1/3.4-dmflow.md
    • part-04-competitive-customer-market/v1/4.1-competitor-ad-analysis.md
    • part-04-competitive-customer-market/v1/4.2-competitor-positioning.md
    • part-04-competitive-customer-market/v1/4.3-customer-analysis.md
    • part-04-competitive-customer-market/v1/4.4-market-analysis.md
  3. Extract material findings. For each source document, identify the 2–5 most strategically consequential findings. Materiality rating: prefer High and Medium; include Low only if the client specifically benefits from confirming.

  4. Synthesise findings into the structured format. Use plain client-facing language, not internal jargon. Each finding stands alone — do not require the client to read the source documents.

  5. Add Open Questions section drawn from the "Open questions" sections of each source document.

  6. Add response mechanism section — instruct the client how to return responses (recommended: produce a paired client-validation-responses.json file alongside the document).

  7. Save the document to:

    engagements/{id}/part-05-client-validation/client-validation-document.md
  8. Generate the response template:

    engagements/{id}/part-05-client-validation/client-validation-responses.template.json

    Containing one entry per finding with empty decision/correction fields.

  9. Mark Part 5 as awaiting_input in _engagement.json (not completed — Part 5 is only complete when the client responses are recorded).

  10. Brief the user on the document, the response mechanism, and the typical 7–14 day decision window.

Recording Client Responses

When the client returns responses (filled-in JSON file or verbal walkthrough captured in a meeting):

  1. Save the populated response file to:

    engagements/{id}/part-05-client-validation/client-validation-responses.json
  2. Run engagement-state.py decision-matrix --validation-file <path> to determine the v2 re-run plan.

  3. Mark Part 5 as completed.

  4. Advance to Part 6 (v2 re-runs).

Quality Discipline

  1. Plain client language. No "MQL/SQL pipeline funnel architecture" jargon. Translate to "the way leads move from interested to ready-to-buy."
  2. Each finding stands alone. Client should not need to consult the source docs to understand the finding.
  3. Evidence is cited explicitly. Vague claims ("market data shows...") are unacceptable. Cite the specific source with the data point.
  4. Materiality is honest. Don't downgrade an uncomfortable finding to "Low" to make it easier to accept.
  5. Open Questions are real questions. Don't fabricate questions for the sake of having an Open Questions section.
  6. The response mechanism is structured. Free-form client emails are hard to translate into Decision Matrix triggers; the JSON response template makes the pattern unambiguous.

Examples

Example 1: Producing the document
User: We've completed Parts 2, 3, 4 for Acme. Time to prepare the Client Validation Document.

Skill response:
1. Verify pre-conditions ✓
2. Pull findings from the 8 source documents (4 from Part 3 + 4 from Part 4) using grep first to locate each category's section, then targeted Read with offset+limit — avoid bulk-Read on all 8 files up front or you'll blow the per-skill 5K-token budget
3. Extract 18 material findings across categories A–F:
   - 4 in Business & SBU
   - 3 in Audience & Segmentation
   - 4 in Positioning & Communications
   - 3 in Channel & Budget
   - 2 in Competitive
   - 2 in Market & Customer
4. 12 are High materiality, 5 Medium, 1 Low
5. 4 Open Questions identified from source docs
6. Save document at engagements/2026-q2/part-05-client-validation/client-validation-document.md (~22 pages)
7. Save response template at engagements/2026-q2/part-05-client-validation/client-validation-responses.template.json
8. Mark Part 5 as awaiting_input
9. Brief: "Document ready. 18 findings, 4 open questions. Recommend client meeting in 5–7 days for live walk-through, with responses returned within 2 weeks."
Example 2: Recording client responses
User: Acme client returned responses. They accepted most but rejected the positioning finding (they want to keep their existing positioning) and added 2 new competitors we missed.

Skill response:
1. Read the populated client-validation-responses.json
2. Categorise responses: 16 ACCEPT, 1 REJECT (positioning), 1 EDIT (competitor list)
3. Determine triggers: positioning_changed + competitors_changed
4. Run engagement-state.py decision-matrix --triggers "positioning_changed,competitors_changed"
5. Output: triggered re-runs = 3.1, 3.2, 3.3, 3.4, 4.1, 4.2 (the union of both triggers' re-run sets)
6. Estimate cost: ~85K tokens
7. Mark Part 5 completed
8. Brief: "Part 5 closed. 6 v2 re-runs triggered. Recommend reviewing the re-run plan and approving before invoking four-core-documents and competitor-analysis with view=v2."
  • engagement-workflow — orchestrates the 12-Part flow
  • four-core-documents — produced the v1 docs being validated; will produce v2 re-runs after Part 5
  • Existing skills/agents competitor-analysis, audience-intelligence, market-intelligence produced the Part 4 docs

© indranilbanerjee, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/client-validation-document of indranilbanerjee/digital-marketing-pro.

Open the folder on GitHubat commit 3343924

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in indranilbanerjee/digital-marketing-pro, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Client Validation Document next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Client Validation Document compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Client Validation Document this skillindranilbanerjee/digital-marketing-pro8541 repos~3.5kAutomated safety check: NotesMIT
Step Partsearthtojake/text-to-cad18k1 repos~1.5kAutomated safety check: PassMIT
Canopy Part Title Blockheygen-com/hyperframes58k1 repos~1kAutomated safety check: PassApache-2.0
Youtube Producercbrock84/headcount2k—~1.3kAutomated safety check: PassMIT
Part Model Maintainerdiscord-php/DiscordPHP1.1k—~3.4kAutomated safety check: PassMIT
Gen Partpartcad/partcad503—~1.9kAutomated safety check: PassApache-2.0

Similar skills

  • Step Parts

    earthtojake/text-to-cad

    Find, evaluate, and download common purchasable CAD parts from step.parts, including named off-the-shelf actuators, servos, motors, electronics boards, connectors, screws, bolts, nuts, washers…

    18k GitHub starsUsed in 1 repo~1.5k tokens
    Backend & APIsAuto-check passed
  • Canopy Part Title Block

    heygen-com/hyperframes

    A HyperFrames video block in which a canopy of leaves sweeps across the frame and parts to reveal two headlines, rendered at 1920×1080 for 12 seconds.

    58k GitHub starsUsed in 1 repo~1k tokens
    Media & CreativeAuto-check passed
  • Youtube Producer

    cbrock84/headcount

    Plans, packages, and scripts long-form video for retention and channel growth — idea selection, titles and thumbnails, script structure, and diagnosing why a video or channel underperforms.

    2k GitHub stars~1.3k tokensUpdated 20 days ago
    Media & CreativeAuto-check passed
  • Part Model Maintainer

    discord-php/DiscordPHP

    Maintain Part domain models — fillable attributes, mutators, typed nested data, save/fetch behavior, permission checks, PHPDoc, and repository bindings.

    1.1k GitHub stars~3.4k tokensUpdated yesterday
    DevelopmentAuto-check passed
  • Gen Part

    partcad/partcad

    Generate a PartCAD part from a natural-language description (and optional reference images/requirements) by authoring a CAD script and validating it with the PartCAD CLI.

    503 GitHub stars~1.9k tokensUpdated today
    Game DevelopmentAuto-check passed
  • STEP Parts Catalog Search

    earthtojake/step.parts

    Searches the step.parts catalog for purchasable CAD parts such as servos, motors, screws and bearings, picks a match and downloads its verified .step file.

    371 GitHub starsUsed in 1 repo~1.1k tokens
    DevelopmentAuto-check passed

More from indranilbanerjee/digital-marketing-pro

All 162 skills in this repo
  • Ab Test Plan

    indranilbanerjee/digital-marketing-pro

    Design a statistically rigorous A/B or multivariate test plan — If/Then/Because hypothesis, control and variant specs, required sample size per variant (absolute vs relative MDE via…

    854 GitHub starsUsed in 1 repo~2k tokens
    Auto-check passed
  • Aeo Audit

    indranilbanerjee/digital-marketing-pro

    Audit how a brand appears across the 6 canonical AI answer surfaces — ChatGPT, Perplexity, Google AI Mode, AI Overviews, Gemini, Copilot — probing 10-25 queries into a numbered output bundle with…

    854 GitHub starsUsed in 1 repo~2.6k tokens
    Auto-check passed
  • Agent Readiness Audit

    indranilbanerjee/digital-marketing-pro

    Audit whether AI agents and AI crawlers can actually use a site — robots.txt rules per AI crawler token (OpenAI, Anthropic and Perplexity bots, Google-Extended, Applebot-Extended)…

    854 GitHub starsUsed in 1 repo~3.9k tokens
    Auto-check passed
  • Backlink Gap

    indranilbanerjee/digital-marketing-pro

    Find referring domains that link to your competitors but not to you, ranked by an outreach-priority score (0.40 DR + 0.25 link-overlap + 0.20 traffic + 0.15 topical relevance) — outputs a four-gate…

    854 GitHub starsUsed in 1 repo~2.8k tokens
    Auto-check passed
  • C2pa Metadata

    indranilbanerjee/digital-marketing-pro

    Embed a C2PA provenance manifest into an AI-generated marketing asset (PNG, JPG, WebP, GIF, TIFF, MP4, MOV, WebM, MP3, WAV, PDF) via scripts/embed-c2pa.py — produces a signed copy of the file…

    854 GitHub starsUsed in 1 repo~2.5k tokens
    Auto-check passed
  • Campaign Audit

    indranilbanerjee/digital-marketing-pro

    Inventory and score everything currently running for a brand across paid search, paid social, email, organic, SEO, AEO/GEO, CRM, and analytics — produces a dated audit document with a 4-tier triage…

    854 GitHub starsUsed in 1 repo~4.1k tokens
    Auto-check: notes

Questions about Client Validation Document

What does Client Validation Document do?

Produce the Part 5 Client Validation Document — the one true stop of the 12-Part engagement where unbiased v1 findings from Parts 2-4 are compiled into 12-25 evidence-cited finding blocks, each…. Client Validation Document is an agent skill from indranilbanerjee/digital-marketing-pro. Produce the Part 5 Client Validation Document — the one true stop of the 12-Part engagement where unbiased v1 findings from Parts 2-4 are compiled into 12-25 evidence-cited finding blocks, each awaiting an ACCEPT / REJECT / EDIT / DEFER client decision, plus a paired JSON response template.

When should I use Client Validation Document?

Client Validation Document fits situations like: /digital-marketing-pro:client-validation-document; prepare v1 findings for client review; run part 5 client validation; the one true stop.

How do I install Client Validation Document in Claude Code?

Run `npx skills add indranilbanerjee/digital-marketing-pro --skill client-validation-document -a claude-code`. Or copy the skill folder (skills/client-validation-document in indranilbanerjee/digital-marketing-pro) into .claude/skills/client-validation-document in your project. Claude Code loads it when a task matches its description.

How do I install Client Validation Document in Codex?

Run `npx skills add indranilbanerjee/digital-marketing-pro --skill client-validation-document -a codex`. Or copy the skill folder (skills/client-validation-document in indranilbanerjee/digital-marketing-pro) into .agents/skills/client-validation-document in your project. Codex loads it when a task matches its description.

Can I use Client Validation Document in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add indranilbanerjee/digital-marketing-pro --skill client-validation-document -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/client-validation-document, .gemini/skills/client-validation-document, .github/skills/client-validation-document and .opencode/skills/client-validation-document in your project.

What does Client Validation Document need to run?

Going by SKILL.md and its folder, Client Validation Document needs the command-line tools its instructions call (python). Our summary lists: Python 3. Its frontmatter pre-approves these tools: Read, Write, Edit, Bash, Glob, Grep.

Does Client Validation Document access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Client Validation Document safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Client Validation Document use?

Client Validation Document is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Client Validation Document use?

About 3.5k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Client Validation Document?

Skills that share tags, products or a category with Client Validation Document: Step Parts (earthtojake/text-to-cad, 18k stars), Canopy Part Title Block (heygen-com/hyperframes, 58k stars), Youtube Producer (cbrock84/headcount, 2k stars) and Part Model Maintainer (discord-php/DiscordPHP, 1.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Client Validation Document?

indranilbanerjee (a GitHub user) maintains it in indranilbanerjee/digital-marketing-pro, which has 854 GitHub stars. The repository holds 162 skills in this directory. The repository was last updated on October 4, 2026.

Source: indranilbanerjee/digital-marketing-pro on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.