Controlling The Snippet Google Shows
Meta descriptions are advisory. For a large share of queries Google discards them and lifts whatever body text matches the query, which is often a cookie notice, a breadcrumb line or the middle of a list. Rewriting the tag again does nothing, because the tag was never the source. The fix is to improve the passage Google is already choosing, or to put a stronger candidate near the top of the page.
FORMAT
snippet-source-control.md
PRIX
Gratuit — sans compte
QUAND S’EN SERVIR
Use when Google ignores your meta description and lifts a stray sentence from the page into the result instead.
Le fichier de compétence
snippet-source-control.md
---
name: snippet-source-control
description: Use when Google ignores your meta description and lifts a stray sentence from the page into the result instead.
---
# Controlling The Snippet Google Shows
Meta descriptions are advisory. For a large share of queries Google discards them and lifts whatever body text matches the query, which is often a cookie notice, a breadcrumb line or the middle of a list. Rewriting the tag again does nothing, because the tag was never the source. The fix is to improve the passage Google is already choosing, or to put a stronger candidate near the top of the page.
## Ce qu’il vous faut d’abord
- The affected queries with the description text as it appears in live results, not as written in the tag
- The rendered page in document order, including anything injected by script before the body copy
- The meta description as served, and the page position for each affected query
## Méthode
1. Search each affected query in a private window with the location set explicitly, and copy the displayed description verbatim. Trackers and preview tools show the tag, so the live result is the only reliable source.
2. Find that exact string in the rendered page. Where it came from is the diagnosis: a body paragraph means Google preferred your copy, boilerplate means it found nothing better to prefer.
3. Compare the text shown for two or three different queries against the same page. Different text per query is normal passage selection and needs a body fix, not a tag fix.
4. Where boilerplate was lifted, look at what sits between the H1 and the first substantive paragraph. Consent text, share prompts and author blocks in the markup ahead of the body are the usual sources.
5. Write two plain sentences in the first 200 words that answer the query directly and use its phrasing. This is the candidate you want selected, and it has to be visible body copy to be eligible.
6. Keep the meta description anyway, around 155 characters, and treat it as the version that survives on brand and navigational queries where the query gives Google nothing to match against.
7. Recheck after a recrawl on the same queries from the same location and device, since snippet selection varies by both.
## Ce que ça produit
A per-query table of lifted text, its source element, and the body edit made to replace it, usually a handful of rows per page.
## Là où ça dérape
- Rewriting the meta description repeatedly when the displayed text never came from it
- Reading the snippet from a rank tracker or a social preview tool, both of which echo the tag rather than the live result
- Judging the fix on one query when selection happens per query, so the page improves for one and stays wrong for the rest
---
Extrait de la bibliothèque de compétences QuQi - https://www.quqi.io/fr/skills/snippet-source-control
Téléchargement gratuit · sans compte, sans e-mail
Ce qu’il vous faut d’abord
-
The affected queries with the description text as it appears in live results, not as written in the tag
-
The rendered page in document order, including anything injected by script before the body copy
-
The meta description as served, and the page position for each affected query
Méthode
-
01
Search each affected query in a private window with the location set explicitly, and copy the displayed description verbatim. Trackers and preview tools show the tag, so the live result is the only reliable source.
-
02
Find that exact string in the rendered page. Where it came from is the diagnosis: a body paragraph means Google preferred your copy, boilerplate means it found nothing better to prefer.
-
03
Compare the text shown for two or three different queries against the same page. Different text per query is normal passage selection and needs a body fix, not a tag fix.
-
04
Where boilerplate was lifted, look at what sits between the H1 and the first substantive paragraph. Consent text, share prompts and author blocks in the markup ahead of the body are the usual sources.
-
05
Write two plain sentences in the first 200 words that answer the query directly and use its phrasing. This is the candidate you want selected, and it has to be visible body copy to be eligible.
-
06
Keep the meta description anyway, around 155 characters, and treat it as the version that survives on brand and navigational queries where the query gives Google nothing to match against.
-
07
Recheck after a recrawl on the same queries from the same location and device, since snippet selection varies by both.
Ce que ça produit
A per-query table of lifted text, its source element, and the body edit made to replace it, usually a handful of rows per page.
Là où ça dérape
-
Rewriting the meta description repeatedly when the displayed text never came from it
-
Reading the snippet from a rank tracker or a social preview tool, both of which echo the tag rather than the live result
-
Judging the fix on one query when selection happens per query, so the page improves for one and stays wrong for the rest
Utiliser cette compétence dans votre propre IA
Le fichier téléchargé est un simple markdown dont l'en-tête porte le nom et le déclencheur. Quand un assistant sait charger des compétences tout seul, c'est cet en-tête qu'il lit pour décider que celle-ci s'applique.
Claude Code
Enregistrez-le sous ~/.claude/skills/snippet-source-control/SKILL.md et Claude le charge tout seul dès que ce que vous faites correspond au déclencheur. Placez-le plutôt dans .claude/skills d'un projet si toute l'équipe doit l'avoir.
Claude
Importez le fichier dans la section compétences de vos réglages. Une fois là, il s'applique tout seul dans toute conversation où le déclencheur colle, sans que vous ayez à y penser.
ChatGPT
Il n'existe pas de format de compétences où l'installer, alors collez le contenu du fichier dans les instructions d'un Projet ou d'un GPT personnalisé. Il s'applique ensuite à toutes les conversations du projet, pas seulement à celle où vous l'avez collé.
Tout le reste
Collez le markdown dans la conversation avant votre question. Cela fonctionne avec n'importe quel assistant, il faut simplement le recoller à chaque fois.
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