Back to Skills

grade-tcg-card

pjt222
Updated 2 days ago
6 views
17
2
17
View on GitHub
Othergeneral

About

This skill grades trading cards (Pokemon, MTG, etc.) using PSA, BGS, or CGC standards through a structured assessment of centering, surface, edges, and corners. It provides a final grade with a confidence interval, useful for pre-screening submissions, settling condition disputes, or estimating value. Developers can integrate it for automated card evaluation workflows.

Quick Install

Claude Code

Recommended
Primary
npx skills add pjt222/agent-almanac -a claude-code
Plugin CommandAlternative
/plugin add https://github.com/pjt222/agent-almanac
Git CloneAlternative
git clone https://github.com/pjt222/agent-almanac.git ~/.claude/skills/grade-tcg-card

Copy and paste this command in Claude Code to install this skill

Documentation

Grade TCG Card

Assess and grade a trading card following professional grading standards (PSA, BGS, CGC). Uses an observation-first protocol adapted from the meditate skill to prevent grade anchoring — the most common grading bias.

When to Use

  • Evaluating a card before submission to a professional grading service
  • Pre-screening a collection to identify high-grade candidates worth submitting
  • Settling disputes about card condition between buyers and sellers
  • Learning to grade consistently by following a structured assessment protocol
  • Estimating the grade-dependent value spread for a specific card

Inputs

  • Required: Card identification (set, number, name, variant/edition)
  • Required: Card images or physical description (front and back)
  • Required: Grading standard to apply (PSA 1-10, BGS 1-10 with subgrades, CGC 1-10)
  • Optional: Known market value at different grades (for grade-value analysis)
  • Optional: Card game (Pokemon, Magic: The Gathering, Flesh and Blood, Kayou)

Procedure

Step 1: Clear Bias — Observation Without Prejudgment

Adapted from meditate Step 2-3: observe the card without anchoring to expected grade or market value.

  1. Set aside any knowledge of the card's market value
  2. Do NOT look up recent sales or population reports before grading
  3. If you know the card is "valuable," acknowledge that bias explicitly:
    • "I know this card is worth $X in PSA 10. I am setting that aside."
  4. Examine the card as a physical object first, not as a collectible
  5. Note your initial gut impression but do NOT let it anchor the assessment
  6. Label any premature grade thoughts as "anchoring" and return to observation

Got: A neutral starting state where the card is assessed purely on physical condition, not market expectations. Grade anchoring (knowing the value before grading) is the #1 source of grading inconsistency.

If fail: If bias feels sticky (a high-value card makes you want to see a 10), write down the bias explicitly. Externalizing it reduces its influence. Proceed only when you can examine the card as a physical object.

Step 2: Centering Assessment

Measure the card's print centering on both faces.

  1. Measure the border width on all four sides of the front face:
    • Left vs. right border (horizontal centering)
    • Top vs. bottom border (vertical centering)
    • Express as ratio: e.g., 55/45 left-right, 60/40 top-bottom
  2. Repeat for the back face
  3. Apply the grading standard's centering thresholds:
PSA Centering Thresholds:
+-------+-------------------+-------------------+
| Grade | Front (max)       | Back (max)        |
+-------+-------------------+-------------------+
| 10    | 55/45 or better   | 75/25 or better   |
| 9     | 60/40 or better   | 90/10 or better   |
| 8     | 65/35 or better   | 90/10 or better   |
| 7     | 70/30 or better   | 90/10 or better   |
+-------+-------------------+-------------------+

BGS Centering Subgrade:
+------+-------------------+-------------------+
| Sub  | Front (max)       | Back (max)        |
+------+-------------------+-------------------+
| 10   | 50/50 perfect     | 50/50 perfect     |
| 9.5  | 55/45 or better   | 60/40 or better   |
| 9    | 60/40 or better   | 65/35 or better   |
| 8.5  | 65/35 or better   | 70/30 or better   |
+------+-------------------+-------------------+
  1. Record the centering score for each axis and the applicable subgrade

Got: Numeric centering ratios for both faces with the corresponding grade/subgrade identified. This is the most objective measurement in the grading process.

If fail: If borders are too narrow to measure accurately (full-art cards, borderless prints), note "centering N/A — borderless" and skip to Step 3. Some grading services apply different standards for borderless cards.

Step 3: Surface Analysis

Examine the card's surface for defects.

  1. Examine the front surface under good lighting:
    • Print defects: ink spots, missing ink, print lines, color inconsistency
    • Surface scratches: visible under direct and angled light
    • Whitening on surface: haze or clouding of the surface layer
    • Indentations or impressions: dents visible under raking light
    • Staining or discoloration: yellowing, water marks, chemical damage
  2. Examine the back surface with the same criteria
  3. Check for factory defects vs. handling damage:
    • Factory: print lines, miscut, crimping — may be less penalized
    • Handling: scratches, dents, stains — always penalized
  4. Rate surface condition:
    • Pristine (10): flawless under magnification
    • Near-pristine (9-9.5): minor imperfections visible only under magnification
    • Excellent (8-8.5): minor wear visible to naked eye
    • Good (6-7): moderate wear, multiple minor defects
    • Fair or below (1-5): significant damage visible

Got: A detailed surface inventory with each defect located, described, and severity-rated. Factory vs. handling defects distinguished.

If fail: If images are too low-resolution for surface analysis, note the limitation and provide a grade range rather than a point grade. Recommend physical inspection.

Step 4: Edge and Corner Evaluation

Assess the card's edges and corners for wear.

  1. Examine all four edges:
    • Whitening: white spots or lines along colored edges (the most common defect)
    • Chipping: small pieces of the edge layer missing
    • Roughness: edge feels uneven or has micro-tears
    • Foil separation: on holofoil cards, check for delamination at edges
  2. Examine all four corners:
    • Sharpness: corner tip is crisp and pointed
    • Rounding: corner tip is worn to a curve (slight, moderate, heavy)
    • Splitting: layer separation visible at corner (dings)
    • Bending: corner turned or creased
  3. Rate edge and corner condition using the same scale as surface
  4. Note which specific corners/edges have the worst condition

Got: Per-edge and per-corner condition assessment. The worst individual corner/edge typically limits the overall grade.

If fail: If the card is in a sleeve or toploader that obscures edges, note which areas couldn't be fully assessed.

Step 5: Assign Final Grade

Combine sub-assessments into the final grade.

  1. For PSA grading (single number 1-10):
    • The final grade is limited by the weakest sub-assessment
    • A card with perfect surface but 65/35 centering caps at PSA 8
    • Apply the "lowest limits" principle, then adjust up if other areas are exceptional
  2. For BGS grading (four subgrades → overall):
    • Assign subgrades: Centering, Edges, Corners, Surface (each 1-10 in 0.5 steps)
    • Overall = weighted average, but the lowest subgrade limits the overall
    • BGS 10 Pristine requires all four subgrades at 10
    • BGS 9.5 Gem Mint requires average of 9.5+ with no subgrade below 9
  3. For CGC grading (similar to PSA with subgrades on label):
    • Assign Centering, Surface, Edges, Corners
    • Overall follows CGC's proprietary weighting
  4. State the final grade with confidence:
    • "PSA 8 (confident)" — clear grade, unlikely to be higher or lower
    • "PSA 8-9 (borderline)" — could go either way at the grading service
    • "PSA 7-8 (uncertain)" — limited assessment data

Got: A final grade with confidence level. For BGS, all four subgrades reported. The grade is supported by evidence from Steps 2-4.

If fail: If the assessment is inconclusive (e.g., can't tell if a surface mark is a scratch or dirt), provide a grade range and recommend professional grading. Never assign a confident grade with insufficient data.

Validation

  • Bias check completed before grading (no grade anchoring)
  • Centering measured on both faces with ratios recorded
  • Surface examined for scratches, print defects, staining, indentations
  • All four edges and corners individually assessed
  • Factory vs. handling defects distinguished
  • Final grade supported by evidence from each sub-assessment
  • Confidence level stated (confident, borderline, uncertain)
  • Grading standard correctly applied (PSA/BGS/CGC thresholds)

Pitfalls

  • Grade anchoring: Knowing a card's value before grading biases the assessment toward the "hoped-for" grade. Assess physically first
  • Ignoring the back: The back surface and back centering count. Many graders over-focus on the front
  • Confusing factory with handling defects: A factory print line is different from a scratch, but both affect the grade
  • Over-grading holofoils: Holographic and foil cards hide surface scratches until viewed at the right angle. Use multiple light angles
  • Centering optical illusions: Art placement can make centering appear better or worse than it is. Measure the borders, not the art

Related Skills

  • build-tcg-deck — Deck building where card condition affects tournament legality
  • manage-tcg-collection — Collection management with grade-based valuation
  • meditate — Source of the observation-without-prejudgment technique adapted for grading bias prevention

GitHub Repository

pjt222/agent-almanac
Path: i18n/caveman-lite/skills/grade-tcg-card
0
agentsagentskillsai-assisted-developmentclaude-codeskillsteams

Related Skills

llamaguard

Other

LlamaGuard is Meta's 7-8B parameter model for moderating LLM inputs and outputs across six safety categories like violence and hate speech. It offers 94-95% accuracy and can be deployed using vLLM, Hugging Face, or Amazon SageMaker. Use this skill to easily integrate content filtering and safety guardrails into your AI applications.

View skill

cost-optimization

Other

This Claude Skill helps developers optimize cloud costs through resource rightsizing, tagging strategies, and spending analysis. It provides a framework for reducing cloud expenses and implementing cost governance across AWS, Azure, and GCP. Use it when you need to analyze infrastructure costs, right-size resources, or meet budget constraints.

View skill

quantizing-models-bitsandbytes

Other

This skill quantizes LLMs to 8-bit or 4-bit precision using bitsandbytes, achieving 50-75% memory reduction with minimal accuracy loss. It's ideal for running larger models on limited GPU memory or accelerating inference, supporting formats like INT8, NF4, and FP4. The skill integrates with HuggingFace Transformers and enables QLoRA training and 8-bit optimizers.

View skill

dispatching-parallel-agents

Other

This Claude Skill dispatches multiple agents to investigate and fix 3+ independent problems concurrently. It is designed for scenarios involving unrelated failures that can be resolved without shared state or dependencies. The core capability is parallel problem-solving, assigning one agent per independent problem domain to maximize efficiency.

View skill